Scientific Work Using or Referencing ELKI

Over the years, ELKI has been increasingly cited/used in scientific publications and other software projects.

The following list is automatically generated from very heterogenous sources, and may contain errors. Where possible, we try to use metadata from DBLP, CrossRef.org, OpenCitations, SemanticScholar, Microsoft Academic Search, and HTML meta headers from the publisher web pages. For theses, seminar articles etc. this approach does however not work. We have not verified every citation discovered by the bot.

2021

  1. Alican Dogan, and Derya Birant (2021). Machine learning and data mining in manufacturing. Expert Systems with Applications 166, 114060, Elsevier BV, 10.1016/j.eswa.2020.114060
  2. L. Erhan, M. Ndubuaku, M. Di Mauro, W. Song, M. Chen, G. Fortino, O. Bagdasar, and A. Liotta (2021). Smart anomaly detection in sensor systems: A multi-perspective review. Information Fusion 67, 64-79, Elsevier BV, 10.1016/j.inffus.2020.10.001
  3. Edouard Fouché, Florian Kalinke, and Klemens Böhm (2021). Efficient subspace search in data streams. Information Systems 97, 101705, Elsevier BV, 10.1016/j.is.2020.101705
  4. Linlin Zong, Faqiang Miao, Xianchao Zhang, Xinyue Liu, and Hong Yu (2021). Incomplete multi-view clustering with partially mapped instances and clusters. Knowledge-Based Systems 212, 106615, Elsevier BV, 10.1016/j.knosys.2020.106615
  5. Prashant Gupta, Aashi Jindal, Jayadeva, and Debarka Sengupta (2021). Linear time identification of local and global outliers. Neurocomputing 429, 141-150, Elsevier BV, 10.1016/j.neucom.2020.11.059
  6. Adriana Tomic, Ivan Tomic, Levi Waldron, Ludwig Geistlinger, Max Kuhn, Rachel L. Spreng, Lindsay C. Dahora, Kelly E. Seaton, Georgia Tomaras, Jennifer Hill, Niharika A. Duggal, Ross D. Pollock, Norman R. Lazarus, Stephen D.R. Harridge, Janet M. Lord, Purvesh Khatri, Andrew J. Pollard, and Mark M. Davis (2021). SIMON: Open-Source Knowledge Discovery Platform. Patterns 2(1), 100178, Elsevier BV, 10.1016/j.patter.2020.100178
  7. Andre F. R. Guarda, Nuno M. M. Rodrigues, and Fernando Pereira (2021). Constant Size Point Cloud Clustering: A Compact, Non-Overlapping Solution. IEEE Transactions on Multimedia 23, 77-91, IEEE, 10.1109/TMM.2020.2974325
  8. John Wamburu, Stephen Lee, Mohammad H. Hajiesmaili, David Irwin, and Prashant Shenoy (2021). Ride Substitution Using Electric Bike Sharing. Feasibility, Cost, and Carbon Analysis. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5(1), 1-28, Association for Computing Machinery (ACM), 10.1145/3448081
  9. Xiaoshen Yin, Alexander S. Martinez, Maria S. Sepúlveda, and Mark R. Christie (2021). Rapid genetic adaptation to recently colonized environments is driven by genes underlying life history traits. BMC Genomics 22(1), Springer Science and Business Media LLC, 10.1186/s12864-021-07553-x
  10. Amin Ganjali Khosrowshahi, Iman Aghayan, Mehmet Metin Kunt, and Abdoul-Ahad Choupani (2021). Detecting crash hotspots using grid and density-based spatial clustering. Proceedings of the Institution of Civil Engineers - Transport, 1-31, Thomas Telford Ltd. 10.1680/jtran.20.00028
  11. Nikolaos Myrtakis, V. Christophides, and Eric Simon (2021). A Comparative Evaluation of Anomaly Explanation Algorithms. EDBT, 10.5441/002/edbt.2021.10

2020

  1. Yanki Aslan, Jan Puskely, Antoine Roederer, and Alexander Yarovoy (2020). Synthesis of quasi‐modular circularly polarized 5G base station antenna arrays based on irregular clustering and sequential rotation. Microwave and Optical Technology Letters, Wiley, 10.1002/mop.32735
  2. Ricardo J. G. B. Campello, Peer Kröger, Jörg Sander, and Arthur Zimek (2020). Density-based clustering. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 10(2), 10.1002/widm.1343, BibTeX
  3. Grzegorz Gołaszewski (2020). Similarity-Based Outlier Detection in Multiple Time Series. Information Technology, Systems Research, and Computational Physics, 116-131, Springer, 10.1007/978-3-030-18058-4_10
  4. Piotr A. Kowalski, Szymon Łukasik, Małgorzata Charytanowicz, and Piotr Kulczycki (2020). Optimizing Clustering with Cuttlefish Algorithm. Information Technology, Systems Research, and Computational Physics, 34-43, Springer, 10.1007/978-3-030-18058-4_3
  5. J. H. Kamdar, J. Jeba Praba, and John J. Georrge (2020). Artificial Intelligence in Medical Diagnosis: Methods, Algorithms and Applications. Machine Learning with Health Care Perspective, 27-37, Springer, 10.1007/978-3-030-40850-3_2
  6. Raneem Qaddoura, Hossam Faris, Ibrahim Aljarah, and Pedro A. Castillo (2020). EvoCluster: An Open-Source Nature-Inspired Optimization Clustering Framework in Python. EvoApplications, 20-36, Springer, 10.1007/978-3-030-43722-0_2, BibTeX
  7. Sasho Nedelkoski, Jasmin Bogatinovski, Ajay Kumar Mandapati, Sören Becker, Jorge Cardoso, and Odej Kao (2020). Multi-source Distributed System Data for AI-Powered Analytics. ESOCC, 161-176, Springer, 10.1007/978-3-030-44769-4_13, BibTeX
  8. Jakub Peschel, Michal Batko, and Pavel Zezula (2020). Algebra for Complex Analysis of Data. DEXA (1), 177-187, Springer, 10.1007/978-3-030-59003-1_12, BibTeX
  9. Erik Thordsen, and Erich Schubert (2020). ABID: Angle Based Intrinsic Dimensionality. SISAP, 218-232, Springer, 10.1007/978-3-030-60936-8_17, BibTeX
  10. Andreas Lang, and Erich Schubert (2020). BETULA: Numerically Stable CF-Trees for BIRCH Clustering. SISAP, 281-296, Springer, 10.1007/978-3-030-60936-8_22, BibTeX
  11. Durgesh Samariya, Sunil Aryal, Kai Ming Ting, and Jiangang Ma (2020). A New Effective and Efficient Measure for Outlying Aspect Mining. WISE (2), 463-474, Springer, 10.1007/978-3-030-62008-0_32, BibTeX
  12. Cédric Buche, Cindy Even, and Julien Soler (2020). Orion: A Generic Model and Tool for Data Mining. Trans. Comput. Sci. 36, 1-25, Springer, 10.1007/978-3-662-61364-1_1, BibTeX
  13. Akanksha Mukhriya, and Rajeev Kumar (2020). Homogeneous Pools to Heterogeneous Ensembles for Unsupervised Outlier Detection. Information, Communication and Computing Technology, 284-295, Springer, 10.1007/978-981-15-9671-1_25
  14. Thomas Ortner, Peter Filzmoser, Maia Rohm, Sarka Brodinova, and Christian Breiteneder (2020). Local projections for high-dimensional outlier detection. METRON, Springer Science and Business Media LLC, 10.1007/S40300-020-00183-5
  15. Hao Wang, Yan Yang, Xiaobo Zhang, and Bo Peng (2020). Parallel multi-view concept clustering in distributed computing. Neural Comput. Appl. 32(10), 5621-5631, 10.1007/s00521-019-04243-4, BibTeX
  16. Ibrahim Aljarah, Majdi M. Mafarja, Ali Asghar Heidari, Hossam Faris, and Seyedali Mirjalili (2020). Clustering analysis using a novel locality-informed grey wolf-inspired clustering approach. Knowl. Inf. Syst. 62(2), 507-539, 10.1007/s10115-019-01358-x, BibTeX
  17. Mohd Yousuf Ansari, Amir Ahmad, Shehroz S. Khan, Gopal Bhushan, and Mainuddin (2020). Spatiotemporal clustering: a review. Artif. Intell. Rev. 53(4), 2381-2423, 10.1007/s10462-019-09736-1, BibTeX
  18. Sevvandi Kandanaarachchi, Mario A. Muñoz, Rob J. Hyndman, and Kate Smith-Miles (2020). On normalization and algorithm selection for unsupervised outlier detection. Data Min. Knowl. Discov. 34(2), 309-354, 10.1007/s10618-019-00661-z, BibTeX
  19. Fatemeh Riahi, and Oliver Schulte (2020). Model-based exception mining for object-relational data. Data Min. Knowl. Discov. 34(3), 681-722, 10.1007/S10618-020-00677-W, BibTeX
  20. Dante Travisany, Eric Goles, Mauricio Latorre, María Paz Cortés, and Alejandro Maass (2020). Generation and robustness of Boolean networks to model Clostridium difficile infection. Nat. Comput. 19(1), 111-134, 10.1007/s11047-019-09730-0, BibTeX
  21. Hien Duy Nguyen, Florence Forbes, and Geoffrey J. McLachlan (2020). Mini-batch learning of exponential family finite mixture models. Stat. Comput. 30(4), 731-748, 10.1007/s11222-019-09919-4, BibTeX
  22. Dannie Korsgaard, Thomas Bjørner, Pernille Krog Sørensen, and Paolo Burelli (2020). Creating user stereotypes for persona development from qualitative data through semi-automatic subspace clustering. User Model. User Adapt. Interact. 30(1), 81-125, 10.1007/s11257-019-09252-5, BibTeX
  23. Raneem Qaddoura, Hossam Faris, and Ibrahim Aljarah (2020). An efficient evolutionary algorithm with a nearest neighbor search technique for clustering analysis. Journal of Ambient Intelligence and Humanized Computing, Springer Science and Business Media LLC, 10.1007/s12652-020-02570-2
  24. Raneem Qaddoura, Hossam Faris, and Ibrahim Aljarah (2020). An efficient clustering algorithm based on the k-nearest neighbors with an indexing ratio. Int. J. Mach. Learn. Cybern. 11(3), 675-714, 10.1007/s13042-019-01027-z, BibTeX
  25. Haofan Zhang, Ke Nian, Thomas F. Coleman, and Yuying Li (2020). Spectral ranking and unsupervised feature selection for point, collective, and contextual anomaly detection. Int. J. Data Sci. Anal. 9(1), 57-75, 10.1007/s41060-018-0161-7, BibTeX
  26. Mariano Kohan, and Juan M. Ale (2020). Discovering traffic congestion through traffic flow patterns generated by moving object trajectories. Comput. Environ. Urban Syst. 80, 101426, 10.1016/j.compenvurbsys.2019.101426, BibTeX
  27. Thiago Orion Simões Amorim, Luke Rendell, Juliana Di Tullio, Eduardo R. Secchi, Franciele R. Castro, and Artur Andriolo (2020). Coda repertoire and vocal clans of sperm whales in the western Atlantic Ocean. Deep Sea Research Part I: Oceanographic Research Papers 160, 103254, Elsevier BV, 10.1016/j.dsr.2020.103254
  28. Francisco García-García, Antonio Corral, Luis Iribarne, and Michael Vassilakopoulos (2020). Improving Distance-Join Query processing with Voronoi-Diagram based partitioning in SpatialHadoop. Future Gener. Comput. Syst. 111, 723-740, 10.1016/j.future.2019.10.037, BibTeX
  29. Tommaso Zoppi, Andrea Ceccarelli, Lorenzo Salani, and Andrea Bondavalli (2020). On the educated selection of unsupervised algorithms via attacks and anomaly classes. J. Inf. Secur. Appl. 52, 102474, 10.1016/J.JISA.2020.102474, BibTeX
  30. Kareem Kamal A. Ghany, Amr Mohamed AbdelAziz, Taysir Hassan A. Soliman, and Adel Abu El-Magd Sewisy (2020). A hybrid modified step Whale Optimization Algorithm with Tabu Search for data clustering. Journal of King Saud University - Computer and Information Sciences, Elsevier BV, 10.1016/j.jksuci.2020.01.015
  31. Qianli Zhao, Linlin Zong, Xianchao Zhang, Xinyue Liu, and Hong Yu (2020). Multi-view clustering via clusterwise weights learning. Knowl. Based Syst. 193, 105459, 10.1016/j.knosys.2019.105459, BibTeX
  32. Linlin Zong, Xianchao Zhang, Xinyue Liu, and Hong Yu (2020). Multi-view clustering on data with partial instances and clusters. Neural Networks 129, 19-30, 10.1016/j.neunet.2020.05.021, BibTeX
  33. Vanel Steve Siyou Fotso, Engelbert Mephu Nguifo, and Philippe Vaslin (2020). Frobenius correlation based u-shapelets discovery for time series clustering. Pattern Recognit. 103, 107301, 10.1016/J.PATCOG.2020.107301, BibTeX
  34. Yuriy Sinyavskiy, Sergey Rylov, and Igor Pestunov (2020). Experimental evaluation of nonparametric clustering algorithms for image segmentation. E3S Web of Conferences 223, 02008, EDP Sciences, 10.1051/e3sconf/202022302008
  35. Shijian Gao (2020). Linear Regression from Uncertain Data and its Applications to Housing Price Prediction. Journal of Physics: Conference Series 1634, 012036, IOP Publishing, 10.1088/1742-6596/1634/1/012036
  36. Olasupo O. Ajayi, Antoine B. Bagula, and Hloniphani Maluleke (2020). Africa 3: A Continental Network Model to Enable the African Fourth Industrial Revolution. IEEE Access 8, 196847-196864, 10.1109/ACCESS.2020.3034144, BibTeX
  37. Alessio Bernardo, Heitor Murilo Gomes, Jacob Montiel, Bernhard Pfahringer, Albert Bifet, and Emanuele Della Valle (2020). C-SMOTE: Continuous Synthetic Minority Oversampling for Evolving Data Streams. 2020 IEEE International Conference on Big Data (Big Data), IEEE, 10.1109/BigData50022.2020.9377768
  38. Lixia Ji, Xiao Zhang, and Lei Zhang (2020). Research on the Algorithm of Education Data Mining Based on Big Data. 2020 IEEE 2nd International Conference on Computer Science and Educational Informatization (CSEI), IEEE, 10.1109/CSEI50228.2020.9142529
  39. Dmytro Progonov, Veronika Prokhorchuk, and Andriy Oliynyk (2020). Evaluation system for user authentication methods on mobile devices. DESSERT, 95-101, IEEE, 10.1109/DESSERT50317.2020.9125076, BibTeX
  40. Manish Mahajan, Santosh Kumar, Bhasker Pant, and Umesh Kumar Tiwari (2020). Incremental Outlier Detection in Air Quality Data Using Statistical Methods. 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), IEEE, 10.1109/ICDABI51230.2020.9325683
  41. Daniyal Kazempour, Long Matthias Yan Peer Kroger, and Thomas Seidl (2020). You see a set of wagons - I see one train: Towards a unified view of local and global arbitrarily oriented subspace clusters. 2020 International Conference on Data Mining Workshops (ICDMW), IEEE, 10.1109/ICDMW51313.2020.00050
  42. Daniyal Kazempour, Anna Beer, Peer Kröger, and Thomas Seidl (2020). I fold you so! An internal evaluation measure for arbitrary oriented subspace clustering. 2020 International Conference on Data Mining Workshops (ICDMW), IEEE, 10.1109/ICDMW51313.2020.00051
  43. Effrosyni Sigala, Efthimios Alepis, and C. Patsakis (2020). Measuring the Quality of Street Surfaces in Smart Cities through Smartphone Crowdsensing. 2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA, 10.1109/IISA50023.2020.9284384
  44. Andreas Züfle, Goce Trajcevski, Dieter Pfoser, and Joon-Seok Kim (2020). Managing Uncertainty in Evolving Geo-Spatial Data. MDM, 5-8, IEEE, 10.1109/MDM48529.2020.00021, BibTeX
  45. Wei Cui, and Wei Yu (2020). A Clustering Approach to Wireless Scheduling. SPAWC, 1-5, IEEE, 10.1109/SPAWC48557.2020.9154271, BibTeX
  46. Jiayun Xu, Yingjiu Li, Robert Deng, and Ke Xu (2020). SDAC: A Slow-Aging Solution for Android Malware Detection Using Semantic Distance Based API Clustering. IEEE Transactions on Dependable and Secure Computing, IEEE, 10.1109/TDSC.2020.3005088
  47. Abdelwahab Boualouache, Sidi-Mohammed Senouci, and Samira Moussaoui (2020). PRIVANET: An Efficient Pseudonym Changing and Management Framework for Vehicular Ad-Hoc Networks. IEEE Trans. Intell. Transp. Syst. 21(8), 3209-3218, 10.1109/TITS.2019.2924856, BibTeX
  48. Hao Wang, Yan Yang, and Bing Liu (2020). GMC: Graph-Based Multi-View Clustering. IEEE Trans. Knowl. Data Eng. 32(6), 1116-1129, 10.1109/TKDE.2019.2903810, BibTeX
  49. Ye-Zheng Liu, Zhe Li, Chong Zhou, Yuanchun Jiang, Jianshan Sun, Meng Wang, and Xiangnan He (2020). Generative Adversarial Active Learning for Unsupervised Outlier Detection. IEEE Trans. Knowl. Data Eng. 32(8), 1517-1528, 10.1109/TKDE.2019.2905606, BibTeX
  50. Gaurav Mishra, and Sraban Mohanty (2020). RDMN: A relative density measure based on MST neighborhood for clustering multi-scale datasets. IEEE Transactions on Knowledge and Data Engineering, IEEE, 10.1109/TKDE.2020.2982400
  51. Liang Zhao, Tao Yang, Jie Zhang, Zhikui Chen, Yi Yang, and Z. Jane Wang (2020). Co-Learning Non-Negative Correlated and Uncorrelated Features for Multi-View Data. IEEE Transactions on Neural Networks and Learning Systems, 1-11, IEEE, 10.1109/TNNLS.2020.2984810
  52. Jifu Zhang, Xiaolong Yu, Yaling Xun, Sulan Zhang, and Xiao Qin (2020). Scalable Mining of Contextual Outliers Using Relevant Subspace. IEEE Trans. Syst. Man Cybern. Syst. 50(3), 988-1002, 10.1109/TSMC.2017.2718592, BibTeX
  53. Omar Iraqi, and Hanan El Bakkali (2020). Immunizer: A Scalable Loosely-Coupled Self-Protecting Software Framework using Adaptive Microagents and Parallelized Microservices. 2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), IEEE, 10.1109/WETICE49692.2020.00013
  54. Bastian Pfeifer, Nikolaos Alachiotis, Pavlos Pavlidis, and Michael G. Schimek (2020). Genome scans for selection and introgression based on k ‐nearest neighbour techniques. Molecular Ecology Resources 20(6), 1597-1609, Wiley, 10.1111/1755-0998.13221
  55. Michael Blumenschein, Xuan Zhang, David Pomerenke, Daniel A. Keim, and Johannes Fuchs (2020). Evaluating Reordering Strategies for Cluster Identification in Parallel Coordinates. Comput. Graph. Forum 39(3), 537-549, 10.1111/CGF.14000, BibTeX
  56. Léonie A. E. Huijser, Vanessa Estrade, Imogen Webster, Laurent Mouysset, Adèle Cadinouche, and Violaine Dulau‐Drouot (2020). Vocal repertoires and insights into social structure of sperm whales ( Physeter macrocephalus ) in Mauritius, southwestern Indian Ocean. Marine Mammal Science 36(2), 638-657, Wiley, 10.1111/MMS.12673
  57. Eugênio F. Cabral, and Robson L. F. Cordeiro (2020). Fast and Scalable Outlier Detection with Sorted Hypercubes. CIKM, 95-104, ACM, 10.1145/3340531.3412033, BibTeX
  58. Massimiliano de Leoni, and Safa Dündar (2020). Event-log abstraction using batch session identification and clustering. SAC, 36-44, ACM, 10.1145/3341105.3373861, BibTeX
  59. Bogdan Burlacu, Gabriel Kronberger, and Michael Kommenda (2020). Operon C++: an efficient genetic programming framework for symbolic regression. GECCO Companion, 1562-1570, ACM, 10.1145/3377929.3398099, BibTeX
  60. Dominik Mautz, Wei Ye, Claudia Plant, and Christian Böhm (2020). Non-Redundant Subspace Clusterings with Nr-Kmeans and Nr-DipMeans. ACM Transactions on Knowledge Discovery from Data 14(5), 1-24, Association for Computing Machinery (ACM), 10.1145/3385652
  61. Weize Kong, Michael Bendersky, Marc Najork, Brandon Vargo, and Mike Colagrosso (2020). Learning to Cluster Documents into Workspaces Using Large Scale Activity Logs. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, ACM, 10.1145/3394486.3403291
  62. Xiaofeng Zhu, Shichao Zhang, Yonghua Zhu, Wei Zheng, and Yang Yang (2020). Self-weighted Multi-view Fuzzy Clustering. ACM Trans. Knowl. Discov. Data 14(4), 48:1-48:17, 10.1145/3396238, BibTeX
  63. Paul Blockhaus, David Broneske, Martin Schäler, Veit Köppen, and Gunter Saake (2020). Combining Two Worlds: MonetDB with Multi-Dimensional Index Structure Support to Efficiently Query Scientific Data. SSDBM, 29:1-29:4, ACM, 10.1145/3400903.3401691, BibTeX
  64. Minh-Ha Le, Md Sakib Nizam Khan, Georgia Tsaloli, Niklas Carlsson, and Sonja Buchegger (2020). AnonFACES. Anonymizing Faces Adjusted to Constraints on Efficacy and Security. Proceedings of the 19th Workshop on Privacy in the Electronic Society, ACM, 10.1145/3411497.3420220
  65. Jakub Peschel, Michal Batko, and Pavel Zezula (2020). Techniques for Complex Analysis of Contemporary Data. Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems, ACM, 10.1145/3415048.3416097
  66. Hannes Rosenbusch, Leon P. Hilbert, Anthony M. Evans, and Marcel Zeelenberg (2020). StatBreak: Identifying “Lucky” Data Points Through Genetic Algorithms. Advances in Methods and Practices in Psychological Science 3(2), 216-228, SAGE Publications, 10.1177/2515245920917950
  67. Todd C. Jacobsen, Kevyn H. Wiskirchen, and Stephen S. Ditchkoff (2020). A novel method for detecting extra-home range movements (EHRMs) by animals and recommendations for future EHRM studies. PLOS ONE 15(11), e0242328, Public Library of Science (PLoS), 10.1371/journal.pone.0242328
  68. Mujeeb Ur Rehman, and Dost Muhammad (2020). Local Neighborhood-based Outlier Detection of High Dimensional Data using different Proximity Functions. International Journal of Advanced Computer Science and Applications 11(4), The Science and Information Organization, 10.14569/IJACSA.2020.0110418
  69. Hanna Wecker, Annemarie Friedrich, and Heike Adel (2020). ClusterDataSplit: Exploring Challenging Clustering-Based Data Splits for Model Performance Evaluation. Proceedings of the First Workshop on Evaluation and Comparison of NLP Systems, Association for Computational Linguistics, 10.18653/v1/2020.eval4nlp-1.15
  70. Charolina Devi Oktaviana Soleman, Nyoman Pramaita, and Made Sudarma (2020). Classification Of Loyality Customer Using K-Means Clustering, Studi Case: PT. Sucofindo (Persero) Denpasar Branch. International Journal of Engineering and Emerging Technology 5(2), 164-171, 10.24843/IJEET.2020.v05.i02.p28
  71. Παναγιώτα Κωτσάκη (2020). Διαχείριση Δεδομένων στις πλατφόρμες ΚΝΙΜE & WEKA. Πανεπιστήμιο Δυτικής Αττικής, 10.26265/polynoe-7
  72. Hanan R. Alnjar (2020). Data visualization metrics between theoretic view and real implementations: A review. DYSONA - Applied Science 1(2), 43-50, E-NAMTILA, 10.30493/das.2020.216111
  73. Marcus Grum, Eldar Sultanow, Daniel Friedmann, André Ullrich, and Norbert Gronau (2020). Tools des Maschinellen Lernens. GITO Verlag, 10.30844/grum_2020
  74. Andre Kummerow, Cristian Monsalve, Christoph Brosinsky, Steffen Nicolai, and Dirk Westermann (2020). A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems. Applied Sciences 10(15), 5209, Mdpi Ag, 10.3390/APP10155209
  75. Christopher Brooke, and Ben Clutterbuck (2020). Mapping Heterogeneous Buried Archaeological Features Using Multisensor Data from Unmanned Aerial Vehicles. Remote. Sens. 12(1), 41, 10.3390/rs12010041, BibTeX
  76. Jian Lin, Guan-hua Du, and Zhiyong Tian (2020). Interval Intuitionistic Fuzzy Clustering Algorithm Based on Symmetric Information Entropy. Symmetry 12(1), 79, 10.3390/SYM12010079, BibTeX
  77. X. Han, C. Armenakis, and M. Jadidi (2020). Dbscan Optimization For Improving Marine Trajectory Clustering And Anomaly Detection. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2020, 455-461, Copernicus GmbH, 10.5194/isprs-archives-xliii-b4-2020-455-2020
  78. Anna Beer, Daniyal Kazempour, Julian Busch, Alexander Tekles, and Thomas Seidl (2020). Grace - Limiting the Number of Grid Cells for Clustering High-Dimensional Data. LWDA, 11-22, CEUR-WS.org, BibTeX
  79. Mo Tiwari, Martin Jinye Zhang, James Mayclin, Sebastian Thrun, Chris Piech, and Ilan Shomorony (2020). Bandit-PAM: Almost Linear Time k-Medoids Clustering via Multi-Armed Bandits. CoRR abs/2006.06856, BibTeX
  80. Erich Schubert, and Peter J. Rousseeuw (2020). Fast and Eager k-Medoids Clustering: O(k) Runtime Improvement of the PAM, CLARA, and CLARANS Algorithms. CoRR abs/2008.05171, BibTeX
  81. Youwei Liang, Dong Huang, Chang-Dong Wang, and Philip S. Yu (2020). Multi-view Graph Learning by Joint Modeling of Consistency and Inconsistency. CoRR abs/2008.10208, BibTeX
  82. Andreas Züfle (2020). Uncertain Spatial Data Management: An Overview. CoRR abs/2009.01121, BibTeX
  83. Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, and Klaus-Robert Müller (2020). A Unifying Review of Deep and Shallow Anomaly Detection. CoRR abs/2009.11732, BibTeX
  84. Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, and Klemens Böhm (2020). Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary. CoRR abs/2009.13853, BibTeX
  85. Сергій Францович Смерічевський, Serhii Frantsovych Smerichevskyi, Л. В. Савченко, and L.V. Savchenko (2020). Clusterization of urban territory for building an effective delivery sustem (Кластеризація міської території для побудови ефективної системи доставки). Wydawnictwo naukowe WSPIA, м. Познань, 978-83-60038-76-5
  86. Axel Elmarsson, and Johan Grundberg (2020). A comparison of different R-tree construction techniques for range queries on neuromorphological data.
  87. Chen Luo (2020). Some Rare LSH Gems for Large-scale Machine Learning. Rice University
  88. Gabriel Matas Barceló (2020). Introducció a l’anàlisi de dades damunt una SmartPlatform. Universitat de les Illes Balears
  89. Georgios Kaiafas (2020). Ensemble Learning For Anomaly Detection With Applications For Cybersecurity And Telecommunication. University of Luxembourg, ​​Luxembourg
  90. Jennifer Carmen Frey (2020). Using data mining to repurpose German language corpora. An evaluation of data-driven analysis methods for corpus linguistics. alma
  91. Larkin Liu (2020). Algorithm for Two-Phase Facility Planning via Balanced Clustering and Integer Programming. arXiv 2009.02736
  92. Mohaddeseh Peyro (2020). The Role of FG Nucleoporins Amino Acid Sequence Composition in Nucleocytoplasmic Transport. UC Berkeley
  93. Pham Van Huong, Le Thi Hong Van, and Pham Sy Nguyen (2020). Detecting Web Attacks Based on Clustering Algorithm and Multi-branch CNN. Journal of Science and Technology on Information security 2(12), 31-37
  94. Larkin Liu (2020). Algorithm for Two-Phase Facility Planning via Balanced Clustering and Integer Programming. arXiv 2009.02736
  95. Tommaso Zoppi, Andrea ceccarelli, Tommaso Capecchi, and Andrea Bondavalli (2020). Unsupervised Anomaly Detectors to Detect Intrusions in the Current Threat Landscape. arXiv 2012.11354
  96. Valerio García Palao (2020). Utilizando Topic Modeling para buscar términos relacionados.
  97. Παναγιώτης Κεχαγιάς (2020). Σχεδιασμός και ανάπτυξη παράλληλου αλγόριθμου συσταδοποίησης στο Apache Spark (Design and development of a parallel clustering algorithm on top of Apache Spark).

2019

  1. Piotr A. Kowalski, Szymon Lukasik, Malgorzata Charytanowicz, and Piotr Kulczycki (2019). Nature Inspired Clustering - Use Cases of Krill Herd Algorithm and Flower Pollination Algorithm. Interactions Between Computational Intelligence and Mathematics (2), 83-98, Springer, 10.1007/978-3-030-01632-6_6, BibTeX
  2. Dipesh Pradhan, and Feroz Zahid (2019). Data Center Clustering for Geographically Distributed Cloud Deployments. AINA Workshops, 1030-1040, Springer, 10.1007/978-3-030-15035-8_101, BibTeX
  3. Zhong Zhang, Chongming Gao, Chongzhi Liu, Qinli Yang, and Junming Shao (2019). Towards Robust Arbitrarily Oriented Subspace Clustering. DASFAA (1), 276-291, Springer, 10.1007/978-3-030-18576-3_17, BibTeX
  4. Altamir Gomes Bispo Junior, and Robson Leonardo Ferreira Cordeiro (2019). Fast and Scalable Outlier Detection with Metric Access Methods. ICCS (2), 189-203, Springer, 10.1007/978-3-030-22741-8_14, BibTeX
  5. Daniel Popovic, Edouard Fouché, and Klemens Böhm (2019). Unsupervised Artificial Neural Networks for Outlier Detection in High-Dimensional Data. ADBIS, 3-19, Springer, 10.1007/978-3-030-28730-6_1, BibTeX
  6. Shuai Wang, Lei Hou, and Meihan Tong (2019). Unsupervised Cross-Lingual Sentence Representation Learning via Linguistic Isomorphism. KSEM (2), 215-226, Springer, 10.1007/978-3-030-29563-9_20, BibTeX
  7. Erich Schubert, and Peter J. Rousseeuw (2019). Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms. SISAP, 171-187, Springer, 10.1007/978-3-030-32047-8_16, BibTeX
  8. Maximilian Archimedes Xaver Hünemörder, Daniyal Kazempour, Peer Kröger, and Thomas Seidl (2019). SIDEKICK: Linear Correlation Clustering with Supervised Background Knowledge. SISAP, 221-230, Springer, 10.1007/978-3-030-32047-8_20, BibTeX
  9. Srikanth Thudumu, Philip Branch, Jiong Jin, and Jugdutt Jack Singh (2019). Adaptive Clustering for Outlier Identification in High-Dimensional Data. ICA3PP (2), 215-228, Springer, 10.1007/978-3-030-38961-1_19, BibTeX
  10. Sudarshan S. Chawathe (2019). Clustering Blockchain Data. Unsupervised and Semi-Supervised Learning, 43-72, Springer, 10.1007/978-3-319-97864-2_3
  11. Dilip Singh Sisodia, Rahul Borkar, and Hari Shrawgi (2019). Performance Evaluation of Large Data Clustering Techniques on Web Robot Session Data. Machine Intelligence and Signal Analysis, 545-553, Springer, 10.1007/978-981-13-0923-6_47
  12. Bilkis Jamal Ferdosi, and Muhammad Masud Tarek (2019). Visual Verification and Analysis of Outliers Using Optimal Outlier Detection Result by Choosing Proper Algorithm and Parameter. Emerging Technologies in Data Mining and Information Security, 507-517, Springer, 10.1007/978-981-13-1498-8_45
  13. Liefa Liao, and Bin Luo (2019). Entropy Isolation Forest Based on Dimension Entropy for Anomaly Detection. Computational Intelligence and Intelligent Systems, 365-376, Springer, 10.1007/978-981-13-6473-0_32
  14. C.S.R. Prabhu, Aneesh Sreevallabh Chivukula, Aditya Mogadala, Rohit Ghosh, and L.M. Jenila Livingston (2019). Big Data Analytics: Systems, Algorithms, Applications. Springer, 10.1007/978-981-15-0094-7
  15. C.S.R. Prabhu, Aneesh Sreevallabh Chivukula, Aditya Mogadala, Rohit Ghosh, and L.M. Jenila Livingston (2019). Intelligent Systems. Big Data Analytics: Systems, Algorithms, Applications, 25-46, Springer, 10.1007/978-981-15-0094-7_2
  16. Laura Aquilanti, Simone Cacace, Fabio Camilli, and Raul De Maio (2019). A Mean Field Games approach to Cluster Analysis. CoRR abs/1907.02261, 10.1007/s00245-019-09646-2, BibTeX
  17. Douglas L. Steinley (2019). Editorial: Journal of Classification Vol. 36-3. J. Classif. 36(3), 393-396, 10.1007/s00357-019-09356-y, BibTeX
  18. Félix Iglesias, Tanja Zseby, Daniel C. Ferreira, and Arthur Zimek (2019). MDCGen: Multidimensional Dataset Generator for Clustering. J. Classif. 36(3), 599-618, 10.1007/S00357-019-9312-3, BibTeX
  19. Daniyal Kazempour, Markus Mauder, Peer Kröger, and Thomas Seidl (2019). Detecting global hyperparaboloid correlated clusters: a Hough-transform based multicore algorithm. Distributed Parallel Databases 37(1), 39-72, 10.1007/s10619-018-7246-0, BibTeX
  20. Ingmar Wiese, Nicole Sarna, Lena Wiese, Araek Tashkandi, and Ulrich Sax (2019). Concept acquisition and improved in-database similarity analysis for medical data. Distributed Parallel Databases 37(2), 297-321, 10.1007/s10619-018-7249-x, BibTeX
  21. Ioan Dragan, Gabriel Iuhasz, and Dana Petcu (2019). A Scalable Platform for Monitoring Data Intensive Applications. J. Grid Comput. 17(3), 503-528, 10.1007/s10723-019-09483-1, BibTeX
  22. Zahid Halim, and Jamal Hussain Khattak (2019). Density-based clustering of big probabilistic graphs. Evol. Syst. 10(3), 333-350, 10.1007/S12530-018-9223-2, BibTeX
  23. Jonathan R. Wells, and Kai Ming Ting (2019). A new simple and efficient density estimator that enables fast systematic search. Pattern Recognit. Lett. 122, 92-98, 10.1016/j.patrec.2018.12.020, BibTeX
  24. Lukasz Struski, Przemyslaw Spurek, Jacek Tabor, and Marek Smieja (2019). Projected memory clustering. Pattern Recognit. Lett. 123, 9-15, 10.1016/j.patrec.2019.02.023, BibTeX
  25. Catia Oliveira, Tiago Guimarães, Filipe Portela, and Manuel Santos (2019). Benchmarking Business Analytics Techniques in Big Data. EUSPN/ICTH, 690-695, Elsevier, 10.1016/j.procs.2019.11.026, BibTeX
  26. Julian Oehling, and David J. Barry (2019). Using machine learning methods in airline flight data monitoring to generate new operational safety knowledge from existing data. Safety Science 114, 89-104, Elsevier BV, 10.1016/j.ssci.2018.12.018
  27. Cui Xie, Mingkui Li, Haoying Wang, and Junyu Dong (2019). A survey on visual analysis of ocean data. Vis. Informatics 3(3), 113-128, 10.1016/J.VISINF.2019.08.001, BibTeX
  28. K. Dingle, A. Zimek, F. Azizieh, and A. R. Ansari (2019). Establishing a many-cytokine signature via multivariate anomaly detection. Scientific Reports 9(1), Springer Science and Business Media LLC, 10.1038/s41598-019-46097-9
  29. Apostolos A. Karanastasis, Gopal S. Kenath, Ravishankar Sundararaman, and Chaitanya K. Ullal (2019). Quantification of functional crosslinker reaction kinetics via super-resolution microscopy of swollen microgels. Soft Matter 15(45), 9336-9342, Royal Society of Chemistry (RSC), 10.1039/C9SM01618J
  30. Pedro Henrique Batista Ruas da Silveira, Alan D. Machado, Michelle C. Silva, Magali R. G. Meireles, Ana Maria Pereira Cardoso, Luis Enrique Zárate, and Cristiane Neri Nobre (2019). Identification and characterisation of Facebook user profiles considering interaction aspects. Behav. Inf. Technol. 38(8), 858-872, 10.1080/0144929X.2019.1566498, BibTeX
  31. Luisa Sanz-Martínez, Erkan Er, Alejandra Martínez-Monés, Yannis Dimitriadis, and Miguel L. Bote-Lorenzo (2019). Creating collaborative groups in a MOOC: a homogeneous engagement grouping approach. Behav. Inf. Technol. 38(11), 1107-1121, 10.1080/0144929X.2019.1571109, BibTeX
  32. Xu Yang, Lingxi Zhu, Sio Lam, Laurie Cuthbert, and Yapeng Wang (2019). Comparison of clustering methods for identification of outdoor measurements in pollution monitoring. IOP Conference Series: Earth and Environmental Science 257, 012014, IOP Publishing, 10.1088/1755-1315/257/1/012014
  33. Hongzhi Wang, Mohamed Jaward Bah, and Mohamed Hammad (2019). Progress in Outlier Detection Techniques: A Survey. IEEE Access 7, 107964-108000, 10.1109/ACCESS.2019.2932769, BibTeX
  34. Maycon Leone Maciel Peixoto, Erick Roseira Pinheiro, Tácito Trindade de Araújo Tiburtino Neves, and Danilo Barbosa Coimbra (2019). Multidimensional Projections Analysis Using Performance Evaluation Planning. BRACIS, 156-161, IEEE, 10.1109/BRACIS.2019.00036, BibTeX
  35. Preeti Mishra, Vijay Varadharajan, Udaya Kiran Tupakula, and Emmanuel S. Pilli (2019). A Detailed Investigation and Analysis of Using Machine Learning Techniques for Intrusion Detection. IEEE Commun. Surv. Tutorials 21(1), 686-728, 10.1109/COMST.2018.2847722, BibTeX
  36. B.S.A.S. Rajita, and Subhrakanta Panda (2019). Community Detection Techniques for Evolving Social Networks. 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence), IEEE, 10.1109/CONFLUENCE.2019.8776896
  37. Arian Soltani, Behzad Akbari, and Nader Mokari (2019). User Profile-based Caching in 5G Telco-CDNs. CloudNet, 1-6, IEEE, 10.1109/CloudNet47604.2019.9064113, BibTeX
  38. Ömer Ibrahim Erduran, Mirjam Minor, Lars Hedrich, Ahmad Tarraf, Frederik Ruehl, and Hans Schroth (2019). Multi-agent Learning for Energy-Aware Placement of Autonomous Vehicles. ICMLA, 1671-1678, IEEE, 10.1109/ICMLA.2019.00273, BibTeX
  39. Abdelwahab Boualouache, Ridha Soua, and Thomas Engel (2019). VPGA: An SDN-based Location Privacy Zones Placement Scheme for Vehicular Networks. IPCCC, 1-8, IEEE, 10.1109/IPCCC47392.2019.8958746, BibTeX
  40. Attila Tiba, Zsombor Bartik, Henrietta Tomán, and András Hajdu (2019). Detecting outlier and poor quality medical images with an ensemble-based deep learning system. ISPA, 99-104, IEEE, 10.1109/ISPA.2019.8868911, BibTeX
  41. Tommaso Zoppi, Andrea Ceccarelli, and Andrea Bondavalli (2019). An Initial Investigation on Sliding Windows for Anomaly-Based Intrusion Detection. SERVICES, 99-104, IEEE, 10.1109/SERVICES.2019.00031, BibTeX
  42. Zhiyong Yang, Qianqian Xu, Weigang Zhang, Xiaochun Cao, and Qingming Huang (2019). Split Multiplicative Multi-View Subspace Clustering. IEEE Trans. Image Process. 28(10), 5147-5160, 10.1109/TIP.2019.2913096, BibTeX
  43. Punit Rathore, Dheeraj Kumar, James C. Bezdek, Sutharshan Rajasegarar, and Marimuthu Palaniswami (2019). A Rapid Hybrid Clustering Algorithm for Large Volumes of High Dimensional Data. IEEE Trans. Knowl. Data Eng. 31(4), 641-654, 10.1109/TKDE.2018.2842191, BibTeX
  44. Wenqiang Cui (2019). Visual Analytics: A Comprehensive Overview. IEEE Access 7, 81555-81573, IEEE, 10.1109/access.2019.2923736
  45. Kaize Ding, Jundong Li, and Huan Liu (2019). Interactive Anomaly Detection on Attributed Networks. WSDM, 357-365, ACM, 10.1145/3289600.3290964, BibTeX
  46. Filipe Falcão, Tommaso Zoppi, Caio Barbosa Viera Silva, Anderson Santos, Baldoino Fonseca, Andrea Ceccarelli, and Andrea Bondavalli (2019). Quantitative comparison of unsupervised anomaly detection algorithms for intrusion detection. SAC, 318-327, ACM, 10.1145/3297280.3297314, BibTeX
  47. Stephen Pauwels, and Toon Calders (2019). An anomaly detection technique for business processes based on extended dynamic bayesian networks. SAC, 494-501, ACM, 10.1145/3297280.3297326, BibTeX
  48. Ambika Shrestha Chitrakar, and Slobodan Petrović (2019). Efficient k-means Using Triangle Inequality on Spark for Cyber Security Analytics. Proceedings of the ACM International Workshop on Security and Privacy Analytics - IWSPA ‘19, ACM Press, 10.1145/3309182.3309187
  49. Gianluigi Folino, Francesco Sergio Pisani, Luigi Pontieri, Pietro Sabatino, and Maryam Amir Haeri (2019). Using genetic programming for combining an ensemble of local and global outlier algorithms to detect new attacks. GECCO (Companion), 167-168, ACM, 10.1145/3319619.3322018, BibTeX
  50. Edouard Fouché, and Klemens Böhm (2019). Monte Carlo Dependency Estimation. SSDBM, 13-24, ACM, 10.1145/3335783.3335795, BibTeX
  51. Daniyal Kazempour, and Thomas Seidl (2019). On systematic hyperparameter analysis through the example of subspace clustering. SSDBM, 226-229, ACM, 10.1145/3335783.3335804, BibTeX
  52. Klaus Arthur Schmid, and Andreas Züfle (2019). Representative Query Answers on Uncertain Data. SSTD, 140-149, ACM, 10.1145/3340964.3340974, BibTeX
  53. Xiaodan Xu, Huawen Liu, and Minghai Yao (2019). Recent Progress of Anomaly Detection. Complex. 2019, 2686378:1-2686378:11, 10.1155/2019/2686378, BibTeX
  54. Omar Iraqi, and Hanan El Bakkali (2019). Application-Level Unsupervised Outlier-Based Intrusion Detection and Prevention. Secur. Commun. Networks 2019, 8368473:1-8368473:13, 10.1155/2019/8368473, BibTeX
  55. Tomáš Farkaš, Jozef Sitarčík, Broňa Brejová, and Mária Lucká (2019). SWSPM: A Novel Alignment-Free DNA Comparison Method Based on Signal Processing Approaches. Evolutionary Bioinformatics 15, 117693431984907, SAGE Publications, 10.1177/1176934319849071
  56. Junpeng Wang, Xiaotong Liu, and Han-Wei Shen (2019). High-dimensional data analysis with subspace comparison using matrix visualization. Inf. Vis. 18(1), 10.1177/1473871617733996, BibTeX
  57. Sanna Aronsson, Henrik Artman, Sinna Lindquist, Mikael Mitchell, Tomas Persson, Robert Ramberg, Mario Romero, and Pontus ter Vehn (2019). Supporting after action review in simulator mission training: Co-creating visualization concepts for training of fast-jet fighter pilots. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 154851291882329, SAGE Publications, 10.1177/1548512918823296
  58. Claes Neuefeind (2019). Muster und Bedeutung: Bedeutungskonstitution als kontextuelle Aktivierung im Vektorraum. Modern Academic Publishing, 10.16994/bam
  59. Daniyal Kazempour, Maksim Kazakov, Peer Kröger, and Thomas Seidl (2019). DICE: Density-based Interactive Clustering and Exploration. BTW, 547-550, Gesellschaft für Informatik, Bonn, 10.18420/btw2019-42, BibTeX
  60. Michael Hahsler, Matthew Piekenbrock, and Derek Doran (2019). dbscan: Fast Density-Based Clustering with R. Journal of Statistical Software 91(1), 1-30, 10.18637/jss.v091.i01
  61. Ahmed Abbood Ali, Ahmed Raee AL-Mhanawi, and Aqeel Kamil Kadhim (2019). Dynamic filtering of malicious records using machine learning integrated databases. Periodicals of Engineering and Natural Sciences (PEN) 7(4), 1667, International University of Sarajevo, 10.21533/pen.v7i4.898
  62. Eka Arriyanti, Ita Arfyanti, and Pitrasacha Adytia (2019). Spatial Coordinate Trial: Converting Non-Spatial Data Dimension for DBSCAN. 2019 6th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), IEEE, 10.23919/EECSI48112.2019.8977130
  63. Zhiqiang Zhang, Yichao Hu, Songtao Ye, Binbin Nie, and Sen Tian (2019). Local linear regression-based unsupervised truth discovery. Intell. Data Anal. 23(3), 573-585, 10.3233/IDA-184106, BibTeX
  64. Lukas Hardi, and Ulrich Wagner (2019). Grocery Delivery or Customer Pickup—Influences on Energy Consumption and CO2 Emissions in Munich. Sustainability 11(3), 641, Mdpi Ag, 10.3390/su11030641
  65. Catherine Dawson (2019). A–Z of Digital Research Methods. Routledge, 10.4324/9781351044677
  66. Xiao Qin, Lei Cao, Elke A. Rundensteiner, and Samuel Madden (2019). Scalable Kernel Density Estimation-based Local Outlier Detection over Large Data Streams. EDBT, 421-432, OpenProceedings.org, 10.5441/002/edbt.2019.37, BibTeX
  67. Daniyal Kazempour, and Thomas Seidl (2019). Insights into a running clockwork: On interactive process-aware clustering. EDBT, 706-709, OpenProceedings.org, 10.5441/002/edbt.2019.92, BibTeX
  68. Alexandr Diadiushkin, Kurt Sandkuhl, and Alexander Maiatin (2019). Fraud Detection in Payments Transactions: Overview of Existing Approaches and Usage for Instant Payments. Complex Syst. Informatics Model. Q. 20, 72-88, 10.7250/csimq.2019-20.04, BibTeX
  69. Wenying Ji (2019). Simulation-Based Analytics for Fabrication Quality-Associated Decision Support. CoRR abs/1903.10565, 10.7939/R3HX16598, BibTeX
  70. Yue Zhao, Zain Nasrullah, and Zheng Li (2019). PyOD: A Python Toolbox for Scalable Outlier Detection. CoRR abs/1901.01588, BibTeX
  71. Erich Schubert, and Arthur Zimek (2019). ELKI: A large open-source library for data analysis - ELKI Release 0.7.5 “Heidelberg”. CoRR abs/1902.03616, BibTeX
  72. Massimiliano de Leoni (2019). From Low-Level Events to Activities - A Session-Based Approach (Extended Version). CoRR abs/1903.03993, BibTeX
  73. Fabien André, Anne-Marie Kermarrec, and Nicolas Le Scouarnec (2019). Derived Codebooks for High-Accuracy Nearest Neighbor Search. CoRR abs/1905.06900, BibTeX
  74. Zhipeng Li, Jianwei Wu, Lin Sun, and Tao Rong (2019). Combinatorial Keyword Recommendations for Sponsored Search with Deep Reinforcement Learning. CoRR abs/1907.08686, BibTeX
  75. Yuening Li, Daochen Zha, Na Zou, and Xia Hu (2019). PyODDS: An End-to-End Outlier Detection System. CoRR abs/1910.02575, BibTeX
  76. Akira Inokuchi, Yusuf Sulistyo Nugroho, Fumiaki Konishi, Hideaki Hata, Akito Monden, and Kenichi Matsumoto (2019). From Academia to Software Development: Publication Citations in Source Code Comments. CoRR abs/1910.06932, BibTeX
  77. Hamed Sarvari, Carlotta Domeniconi, Bardh Prenkaj, and Giovanni Stilo (2019). Unsupervised Boosting-based Autoencoder Ensembles for Outlier Detection. CoRR abs/1910.09754, BibTeX
  78. Maximilian Franzke (2019). Querying and mining heterogeneous spatial, social, and temporal data. Ludwig Maximilian University of Munich, Germany, BibTeX
  79. Marwan Kilani (2019). Appendices. Byblos in the Late Bronze Age, Brill, 978-90-04-41660-4
  80. Hana Řezanková, and Richard Novák (2019). Effect of ordinal variable transformations on hierarchical clustering results: A case study on the Big Data phenomenon. 22nd International Scientific Conference on Applications of Mathematics and Statistics in Economics (AMSE 2019), Atlantis Press, 978-94-6252-804-8
  81. Rebecca Lee Hammons, and Ronald J. Kovac (2019). Fundamentals of Internet of Things for Non-Engineers. CRC Press, 9781000000344
  82. Adrià Correas Grifoll (2019). Study and implementation of Machine Learning algorithms optimized for distributed multidimensional indexing databases. Universitat Politècnica de Catalunya
  83. Altamir Gomes Bispo Junior (2019). Fast and Scalable Outlier Detection with Metric Access Methods. Biblioteca Digital de Teses e Dissertações da Universidade de São Paulo
  84. Anderson Santos da Silva (2019). A framework of unsupervised techniques for anomaly-based intrusion detection (Um framework de técnicas não supervisionadas para detecção de intrusão baseada em anomalias). Universidade Federal de Alagoas
  85. Anis Sharafoddini (2019). Toward Precision Medicine in Intensive Care: Leveraging Electronic Health Records and Patient Similarity. University of Waterloo
  86. Anna Ruggero (2019). Entity search: How to build virtual documents leveraging on graph embeddings.
  87. Benjamin Heinzerling (2019). Aspects of Coherence for Entity Analysis.
  88. Boleslo Edward Romero (2019). Identifying Geographical Features with Spatial Data: Multi-scale Approaches for Representing Local Extrema. UC Santa Barbara
  89. Denis A. SYROMYATNIKOV, Darya A. PYATKINA, Larisa N. KONDRATENKO, Sergey I. KRIVOLAPOV, and Diana I. STEPANOVA (2019). Big data analysis for studying water supply and sanitation coverage in cities. Revista ESPACIOS 40(27)
  90. Emeli Pettersson, and Albin Carlson (2019). Att hitta en nål i en höstack: Metoder och tekniker för att sålla och gradera stora mängder ostrukturerad textdata (Finding a Needle in a Haystack: Methods and techniques for screening and grading large amounts of unstructured textual data). Malmö universitet/Teknik och samhälle
  91. Guansong Pang (2019). Non-IID outlier detection with coupled outlier factors.
  92. Hatice AKTAŞ GÖKÇE (2019). Yapay Sinir Ağları ile Robotik Cerrahi Operasyonu Geçirmiş Prostat Kanserli Bireylerde Nüks Durumunun İncelenmesi (Investigation of the Recurrence Status in Prostate Cancer Individuals with Robotic Surgery with Artificial Neural Network). Ankara Yıldırım Beyazıt Üniversitesi Sağlık Bilimleri Enstitüsü
  93. Igor Wescley Silva de Freitas (2019). Um estudo comparativo de técnicas de detecção de outliers no contexto de classificação de dados. Universidade Federal Rural do Semi-Árido
  94. José David Jácome Escobar, and Estalin Augusto Viracocha Andrade (2019). Desarrollo de una aplicación para detección de patrones en imágenes mediante el uso de aprendizaje profundo. Quito: UCE
  95. Lars Jürgensen (2019). Clustering and Analysis of User Behaviors utilizing a Graph Edit Distance Metric. 48, Kiel University
  96. Marie Ernst (2019). Contributions to spatial data analysis and Stein’s method. Université de Liège, ​Liège, ​​Belgique
  97. Marián Lamr (2019). Včasné varování před zvýšeným rizikem vzniku dopravní nehody s využitím data miningu.
  98. Matthew C. Recker (2019). Enabling Mobile Neutron Detection Systems with CLYC. Air Force Institute of Technology
  99. Patrícia Freitas Pelozo Hespanhol (2019). Análise de padrões na produção de cana de açúcar utilizando aprendizado de máquina (Analysis on sugar cane production using machine learning). Universidade Estadual Paulista (UNESP)
  100. Sebastian Letschert (2019). Quantitative Analysis of Membrane Components using Super-Resolution Microscopy. Universität Würzburg, Fakultät für Biologie
  101. Xiao Yi, Mircea Scutariu, and Kenneth Smith (2019). Optimisation of offshore wind farm inter-array collection system. IET Renewable Power Generation 13(11), 1990-1999, IET Digital Library
  102. Yikai Gong (2019). A big data infrastructure for real-time traffic analytics on the cloud.
  103. Παναγιώτης Διέννης, and Αλέξανδρος Μπολοβίνος (2019). Εργαλεία ανάλυσης και οπτικοποίησης δεδομένων σε συστήματα επιχειρηματικής ευφυΐας. ΤΕΙ Δυτικής Ελλάδας
  104. 丁志成, DING Zhicheng, 葛洪伟, GE Hongwei, 周竞, and ZHOU Jing (2019). 基于Kl散度的密度峰值聚类算法. 重庆邮电大学学报(自然科学版)
  105. 程绵绵, CHENG Mianmian, 孙群, SUN Qun, 李少梅, LI Shaomei, 徐立, and XU Li (2019). 顾及密度对比的多层次聚类点群选取方法. 武汉大学学报·信息科学版

2018

  1. Arthur Zimek, and Peter Filzmoser (2018). There and back again: Outlier detection between statistical reasoning and data mining algorithms. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 8(6), 10.1002/widm.1280, BibTeX
  2. Arthur Zimek, and Erich Schubert (2018). Outlier Detection. Encyclopedia of Database Systems (2nd ed.), Springer, 10.1007/978-1-4614-8265-9_80719, BibTeX
  3. Mark Wickham (2018). Machine Learning Environments. Practical Java Machine Learning, 227-295, Apress, 10.1007/978-1-4842-3951-3_5
  4. Huixiao Hong, Jieqiang Zhu, Minjun Chen, Ping Gong, Chaoyang Zhang, and Weida Tong (2018). Quantitative Structure–Activity Relationship Models for Predicting Risk of Drug-Induced Liver Injury in Humans. Drug-Induced Liver Toxicity, 77-100, Springer, 10.1007/978-1-4939-7677-5_5
  5. Adam Byron (2018). Proteomic Profiling of Integrin Adhesion Complex Assembly. Methods in Molecular Biology, 193-236, Springer, 10.1007/978-1-4939-7759-8_13
  6. Michael E. Houle, Erich Schubert, and Arthur Zimek (2018). On the Correlation Between Local Intrinsic Dimensionality and Outlierness. SISAP, 177-191, Springer, 10.1007/978-3-030-02224-2_14, BibTeX
  7. Michael Richter, Jürgen Hermes, and Claes Neuefeind (2018). Aspectual Classifications: Use of Raters’ Associations and Co-occurrences of Verbs for Aspectual Classification in German. ICAART (Revised Selected Papers), 467-491, Springer, 10.1007/978-3-030-05453-3_22, BibTeX
  8. Arno G. Stefani, Achim Sandmann, Andreas Burkovski, Johannes B. Huber, Heinrich Sticht, and Christophe Jardin (2018). Application of Methods from Information Theory in Protein-Interaction Analysis. Lecture Notes in Bioengineering, 293-313, Springer, 10.1007/978-3-319-54729-9_13
  9. Helmut Neukirchen (2018). Elephant Against Goliath: Performance of Big Data Versus High-Performance Computing DBSCAN Clustering Implementations. Simulation Science, 251-271, Springer, 10.1007/978-3-319-96271-9_16
  10. Meiling Zhu, Chen Liu, and Yanbo Han (2018). An Event Correlation Based Approach to Predictive Maintenance. APWeb/WAIM (2), 232-247, Springer, 10.1007/978-3-319-96893-3_18, BibTeX
  11. Alberto Fernández, Salvador García, Mikel Galar, Ronaldo C. Prati, Bartosz Krawczyk, and Francisco Herrera (2018). Data Intrinsic Characteristics. Learning from Imbalanced Data Sets, 253-277, Springer, 10.1007/978-3-319-98074-4_10
  12. Salma Jamal, Sukriti Goyal, Abhinav Grover, and Asheesh Shanker (2018). Machine Learning: What, Why, and How?. Bioinformatics: Sequences, Structures, Phylogeny, 359-374, Springer, 10.1007/978-981-13-1562-6_16
  13. Ahmed AlEroud, and Aryya Gangopadhyay (2018). Multimode co-clustering for analyzing terrorist networks. Inf. Syst. Frontiers 20(5), 1053-1074, 10.1007/s10796-016-9712-4, BibTeX
  14. Jakub Sawicki, Marcin Los, Maciej Smolka, Robert Schaefer, and Julen Álvarez-Aramberri (2018). Approximating landscape insensitivity regions in solving ill-conditioned inverse problems. Memetic Comput. 10(3), 279-289, 10.1007/s12293-018-0258-5, BibTeX
  15. Joice K. Joseph, Karunakaran Akhil Dev, A.P. Pradeepkumar, and Mahesh Mohan (2018). Big Data Analytics and Social Media in Disaster Management. Integrating Disaster Science and Management, 287-294, Elsevier, 10.1016/B978-0-12-812056-9.00016-6
  16. Anitha Ramchandran, and Arun Kumar Sangaiah (2018). Unsupervised Anomaly Detection for High Dimensional Data—an Exploratory Analysis. Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications, 233-251, Elsevier, 10.1016/B978-0-12-813314-9.00011-6
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2017

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  7. Jakub Sawicki, Maciej Smolka, Marcin Los, Robert Schaefer, and Piotr Faliszewski (2017). Two-Phase Strategy Managing Insensitivity in Global Optimization. EvoApplications (1), 266-281, 10.1007/978-3-319-55849-3_18, BibTeX
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  11. Jyoti Lakhani, Ajay Khuteta, Anupama Choudhary, and Dharmesh Harwani (2017). Hierarchical Clustering-Based Algorithms and In Silico Techniques for Phylogenetic Analysis of Rhizobia. Rhizobium Biology and Biotechnology, 185-214, Springer, 10.1007/978-3-319-64982-5_10
  12. Luisa Sanz-Martínez, Alejandra Martínez-Monés, Miguel L. Bote-Lorenzo, Juan Alberto Muñoz-Cristóbal, and Yannis A. Dimitriadis (2017). Automatic Group Formation in a MOOC Based on Students’ Activity Criteria. EC-TEL, 179-193, Springer, 10.1007/978-3-319-66610-5_14, BibTeX
  13. Adnan R. Manzoor, Julia S. Mollee, Aart Tijmen van Halteren, and Michel C. A. Klein (2017). Real-Life Validation of Methods for Detecting Locations, Transition Periods and Travel Modes Using Phone-Based GPS and Activity Tracker Data. ICCCI (1), 473-483, Springer, 10.1007/978-3-319-67074-4_46, BibTeX
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  18. Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2017). The (black) art of runtime evaluation: Are we comparing algorithms or implementations?. Knowl. Inf. Syst. 52(2), 341-378, 10.1007/s10115-016-1004-2, BibTeX
  19. Junming Shao, Xinzuo Wang, Qinli Yang, Claudia Plant, and Christian Böhm (2017). Synchronization-based scalable subspace clustering of high-dimensional data. Knowl. Inf. Syst. 52(1), 83-111, 10.1007/s10115-016-1013-1, BibTeX
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  21. Klaus Arthur Schmid, Andreas Züfle, Tobias Emrich, Matthias Renz, and Reynold Cheng (2017). Uncertain Voronoi cell computation based on space decomposition. GeoInformatica 21(4), 797-827, 10.1007/S10707-017-0293-2, BibTeX
  22. Mohamed Ben Khalifa, Rebeca P. Díaz Redondo, Ana Fernández Vilas, and Sandra Servia Rodríguez (2017). Identifying urban crowds using geo-located Social media data: a Twitter experiment in New York City. J. Intell. Inf. Syst. 48(2), 287-308, 10.1007/s10844-016-0411-x, BibTeX
  23. Kai Ming Ting, Takashi Washio, Jonathan R. Wells, and Sunil Aryal (2017). Defying the gravity of learning curve: a characteristic of nearest neighbour anomaly detectors. Mach. Learn. 106(1), 55-91, 10.1007/s10994-016-5586-4, BibTeX
  24. Seyed Morteza Mousavi, Aaron Harwood, Shanika Karunasekera, and Mojtaba Maghrebi (2017). Geometry of interest (GOI): spatio-temporal destination extraction and partitioning in GPS trajectory data. J. Ambient Intell. Humaniz. Comput. 8(3), 419-434, 10.1007/s12652-016-0400-5, BibTeX
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  26. Susanna Spinsante, Vera Stara, Elisa Felici, Laura Montanini, Laura Raffaeli, Lorena Rossi, and Ennio Gambi (2017). The Human Factor in the Design of Successful Ambient Assisted Living Technologies. Ambient Assisted Living and Enhanced Living Environments, 61-89, Elsevier, 10.1016/B978-0-12-805195-5.00004-1
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  29. William M. Trochim (2017). Hindsight is 20/20: Reflections on the evolution of concept mapping. Evaluation and Program Planning 60, 176-185, Elsevier BV, 10.1016/j.evalprogplan.2016.08.009
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  34. Alvin Chiang, Esther David, Yuh-Jye Lee, Guy Leshem, and Yi-Ren Yeh (2017). A study on anomaly detection ensembles. J. Appl. Log. 21, 1-13, 10.1016/j.jal.2016.12.002, BibTeX
  35. Dominik Sacha, Michael Sedlmair, Leishi Zhang, John Aldo Lee, Jaakko Peltonen, Daniel Weiskopf, Stephen C. North, and Daniel A. Keim (2017). What you see is what you can change: Human-centered machine learning by interactive visualization. Neurocomputing 268, 164-175, 10.1016/j.neucom.2017.01.105, BibTeX
  36. Linlin Zong, Xianchao Zhang, Long Zhao, Hong Yu, and Qianli Zhao (2017). Multi-view clustering via multi-manifold regularized non-negative matrix factorization. Neural Networks 88, 74-89, 10.1016/j.neunet.2017.02.003, BibTeX
  37. Marcin Los, Jakub Sawicki, Maciej Smolka, and Robert Schaefer (2017). Memetic approach for irremediable ill-conditioned parametric inverse problems. ICCS, 867-876, Elsevier, 10.1016/j.procs.2017.05.007, BibTeX
  38. Qing Tian, and Maria Carmen Lemos (2017). Household Livelihood Differentiation and Vulnerability to Climate Hazards in Rural China. World Development, Elsevier BV, 10.1016/j.worlddev.2017.10.019
  39. Hannes Bitto, Beatrice Mörstedt, Sylvia Faschina, and Rolf-Dieter Stieglitz (2017). ADHS bei Erwachsenen. Ein dimensionales oder kategoriales Konstrukt?. Zeitschrift für Psychiatrie, Psychologie und Psychotherapie 65(2), 121-131, Hogrefe Publishing Group, 10.1024/1661-4747/a000311
  40. Ricardo de Souza Jacomini, David Correa Martins Jr., Felipe Leno da Silva, and Anna Helena Reali Costa (2017). GeNICE: A Novel Framework for Gene Network Inference by Clustering, Exhaustive Search, and Multivariate Analysis. J. Comput. Biol. 24(8), 809-830, 10.1089/cmb.2017.0022, BibTeX
  41. Fernando Perez-Sanz, Pedro J. Navarro, and Marcos Egea-Cortines (2017). Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms. GigaScience, Oxford University Press (OUP), 10.1093/gigascience/gix092
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  47. Roselyn Isimeto, Chika Yinka-Banjo, Charles O. Uwadia, and Daniel C. Alienyi (2017). An enhanced clustering analysis based on glowworm swarm optimization. 2017 IEEE 4th International Conference on Soft Computing & Machine Intelligence (ISCMI), IEEE, 10.1109/ISCMI.2017.8279595
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  58. Dominik Mautz, Wei Ye, Claudia Plant, and Christian Böhm (2017). Towards an Optimal Subspace for K-Means. KDD, 365-373, ACM, 10.1145/3097983.3097989, BibTeX
  59. Suhang Wang, Charu C. Aggarwal, and Huan Liu (2017). Randomized Feature Engineering as a Fast and Accurate Alternative to Kernel Methods. KDD, 485-494, ACM, 10.1145/3097983.3098001, BibTeX
  60. Wubai Zhou, Wei Xue, Ramesh Baral, Qing Wang, Chunqiu Zeng, Tao Li, Jian Xu, Zheng Liu, Larisa Shwartz, and Genady Ya. Grabarnik (2017). STAR: A System for Ticket Analysis and Resolution. KDD, 2181-2190, ACM, 10.1145/3097983.3098190, BibTeX
  61. Guansong Pang, Hongzuo Xu, Longbing Cao, and Wentao Zhao (2017). Selective Value Coupling Learning for Detecting Outliers in High-Dimensional Categorical Data. CIKM, 807-816, ACM, 10.1145/3132847.3132994, BibTeX
  62. Mattia Zeni, and Komminist Weldemariam (2017). Extracting information from newspaper archives in Africa. IBM J. Res. Dev. 61(6), 12, 10.1147/JRD.2017.2742706, BibTeX
  63. Zhihua Li, Ziyuan Li, Ning Yu, and Steven Wen (2017). Locality-Based Visual Outlier Detection Algorithm for Time Series. Secur. Commun. Networks 2017, 1869787:1-1869787:10, 10.1155/2017/1869787, BibTeX
  64. Changbo Ke, Zhiqiu Huang, Fu Xiao, and Linyuan Liu (2017). Privacy Data Decomposition and Discretization Method for SaaS Services. Mathematical Problems in Engineering 2017, 1-11, Hindawi Limited, 10.1155/2017/4785142
  65. Ricardo de Souza Jacomini (2017). Inferência de redes gênicas por agrupamento, busca exaustiva e análise de predição intrinsecamente multivariada. University of São Paulo, Brazil, 10.11606/T.3.2017.tde-05092017-111639, BibTeX
  66. Eugene Lemuel R. Garcia (2017). Bitcoin Transaction Tracing and Purchasing Behavior Characterization of Online Anonymous Marketplaces Using Side Channels. Carnegie Mellon University, 10.1184/R1/6723071.v1
  67. 迟荣华, 程媛, 朱素霞, 黄少滨, and 陈德运 (2017). 基于快速高斯变换的不确定数据聚类算法. 通信学报 38(3), 101-111, 10.11959/j.issn.1000-436x.2017061
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  69. Guillaume Casanova, Elias Englmeier, Michael E. Houle, Peer Kröger, Michael Nett, Erich Schubert, and Arthur Zimek (2017). Dimensional Testing for Reverse k-Nearest Neighbor Search. Proc. VLDB Endow. 10(7), 769-780, 10.14778/3067421.3067426, BibTeX
  70. Lu Chen, Yunjun Gao, Baihua Zheng, Christian S. Jensen, Hanyu Yang, and Keyu Yang (2017). Pivot-based Metric Indexing. Proc. VLDB Endow. 10(10), 1058-1069, 10.14778/3115404.3115411, BibTeX
  71. Burak Omer Saracoglu (2017). Location selection factors of small hydropower plant investments powered by SAW, grey WPM and fuzzy DEMATEL based on human natural language perception. International Journal of Renewable Energy Technology 8(1), 1, Inderscience Publishers, 10.1504/IJRET.2017.080867
  72. Igor A. Pestunov, , Sergey A. Rylov, Yuriy N. Sinyavskiy, Vladimir B. Berikov, , , and (2017). Computationally efficient methods of clustering ensemble construction for satellite image segmentation. Image Processing, Geoinformation Technology and Information Security, Samara University, 10.18287/1613-0073-2017-1901-194-200
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  75. Danfeng (Daphne) Yao, Xiaokui Shu, Long Cheng, and Salvatore J. Stolfo (2017). Anomaly Detection as a Service: Challenges, Advances, and Opportunities. Anomaly Detection as a Service Synthesis Lectures on Information Security, Privacy, and Trust, Morgan & Claypool Publishers, 10.2200/S00800ED1V01Y201709SPT022, BibTeX
  76. Jürgen Bernard, Eduard Dobermann, Michael Sedlmair, and Dieter W. Fellner (2017). Combining Cluster and Outlier Analysis with Visual Analytics. EuroVA@EuroVis, 19-23, Eurographics Association, 10.2312/eurova.20171114, BibTeX
  77. Wubai Zhou (2017). Data Mining Techniques to Understand Textual Data. Florida International University, 10.25148/etd.FIDC003998
  78. Leonidas Tsekouras, Iraklis Varlamis, and George Giannakopoulos (2017). A Graph-based Text Similarity Measure That Employs Named Entity Information. RANLP, 765-771, INCOMA Ltd. 10.26615/978-954-452-049-6_098, BibTeX
  79. Julien F. Marquant, L. Andrew Bollinger, Ralph Evins, and Jan Carmeliet (2017). A new combined clustering method to analyse the potential of district heating networks at large-scale. 30th International Conference on Efficiency, Cost, Optimisation, Simulation and Environmental Impact of Energy Systems (ECOS 2017), ETH Zurich, 10.3929/ethz-b-000196118
  80. Yasser Abd Djawad, Andi Mu’nisa, Pangayoman Rusung, Abdi Kurniawan, Irma Suryani Idris, and Mushawwir Taiyeb (2017). Essential Feature Extraction of Photoplethysmography Signal of Men and Women in Their 20s. Engineering Journal 21(4), 259-272, Faculty of Engineering, Chulalongkorn University, 10.4186/ej.2017.21.4.259
  81. Jaakko Peltonen, and Ziyuan Lin (2017). Parallel Coordinate Plots for Neighbor Retrieval. VISIGRAPP (3: IVAPP), 40-51, SciTePress, 10.5220/0006097400400051, BibTeX
  82. Linnea Passing, Manuel Then, Nina Hubig, Harald Lang, Michael Schreier, Stephan Günnemann, Alfons Kemper, and Thomas Neumann (2017). SQL- and Operator-centric Data Analytics in Relational Main-Memory Databases. EDBT, 84-95, OpenProceedings.org, 10.5441/002/edbt.2017.09, BibTeX
  83. Zachary M. Jullion (2017). A New Method for Semi-Supervised Density-Based Projected Clustering. University of Alberta, 10.7939/R3VH5CZ0S
  84. S Sathappan, S Sridhar, and D Tomar (2017). A Literature Study on Traditional Clustering Algorithms for Uncertain Data. British Journal of Mathematics & Computer Science 21(5), 1-21, Sciencedomain International, 10.9734/BJMCS/2017/32697
  85. Luisa Sanz-Martínez, Juan Alberto Muñoz-Cristóbal, Miguel L. Bote-Lorenzo, Alejandra Martínez-Monés, and Yannis A. Dimitriadis (2017). Toward Criteria-Based Automatic Group Formation in MOOCs. EMOOCs-WIP, 83-88, CEUR-WS.org, BibTeX
  86. Chen Luo, and Anshumali Shrivastava (2017). Arrays of (locality-sensitive) Count Estimators (ACE): High-Speed Anomaly Detection via Cache Lookups. CoRR abs/1706.06664, BibTeX
  87. Jonathan R. Wells, and Kai Ming Ting (2017). A simple efficient density estimator that enables fast systematic search. CoRR abs/1707.00783, BibTeX
  88. Erich Schubert, Andreas Spitz, Michael Weiler, Johanna Geiß, and Michael Gertz (2017). Semantic Word Clouds with Background Corpus Normalization and t-distributed Stochastic Neighbor Embedding. CoRR abs/1708.03569, BibTeX
  89. Wenying Ji, Simaan M. AbouRizk, Osmar R. Zaïane, and Yitong Li (2017). A Hybrid Data Mining Approach for Product Complexity Analysis. CoRR abs/1710.10555, BibTeX
  90. Dimitra Papadimitriou (2017). Extraction and Exploitation of User Goals and Intentions for Querying and Recommendation. University of Trento, Italy, BibTeX
  91. Nina Hubig (2017). Analyzing and Predicting Large Vector-, Graph- and Spatio-Temporal Data. Technical University Munich, Germany, BibTeX
  92. Markus Mauder (2017). Analyzing complex data using domain constraints. Ludwig Maximilian University of Munich, Germany, BibTeX
  93. Samuel Maurus (2017). Exploratory Knowledge-Mining from Complex Data Contexts in Linear Time. Technical University Munich, Germany, BibTeX
  94. Julien Collet (2017). Exploration of parallel graph-processing algorithms on distributed architectures. (Exploration d’algorithmes de traitement parallèle de graphes sur architectures distribuées). University of Technology of Compiègne, France, BibTeX
  95. Dr. Uday Kamath, and Krishna Choppella (2017). Mastering Java Machine Learning. Packt Publishing Ltd, 9781785888557
  96. Leandro Nunes De Castro Silva Daniel Gomes Ferrari (2017). Introdução a mineração de dados. Editora Saraiva, 9788547200992
  97. A. Manzoor (2017). Minding a Healthy Lifestyle: An Exploration of Mental Processes and a Smart Environment to Provide Support for a Healthy Lifestyle. Amsterdam: Vrije Universiteit
  98. Aakash Ravi (2017). Machine learning-based identification of separating features in molecular fragments.
  99. Alonso Vallejos-Peña (2017). Propuesta de algoritmo que combina el agrupamiento en subespacios basado en densidad y el agrupamiento basado en restricciones para la detección de grupos que incluyan atributos de interés en conjuntos de datos de alta dimensionalidad. Instituto Tecnológico de Costa Rica
  100. Andreas Forstén (2017). Unsupervised Anomaly Detection in Receipt Data.
  101. Anthony McCaffrey, and University of Massachusetts (UMass) (2017). Feature Type Spectrum Technique.
  102. Dana Yarden, Oded Shoseyov, Merav Blanca, and Gemmacert Ltd (2017). System and method for qualifying plant material.
  103. Daniel Bauersachs (2017). Interactive Association Rule Exploration. Ludwig-Maximilians-Universität München
  104. Evgeniy A. Malyutin, Dmitriy Yu. Bugaichenko, and Alexey N. Mishenin (2017). Textual trends detection at OK. St Petersburg State University
  105. George E. Barreto, Rosa M. Gomez, Rosa H. Bustos, Diego A. Forero, Gjumrakch Aliev, Vadim V. Tarasov, Nagendra S. Yarla, Valentina Echeverria, and Janneth Gonzalez (2017). Approaches of the Transcriptomic Analysis in Astrocytes: Potential Pharmacological Targets. Bentham Science Publishers
  106. Ilari Kampman (2017). Algorithms for Clustering High-Dimensional Data (Algoritmeja moniulotteisen datan klusterointiin).
  107. Julien Collet (2017). Exploration of parallel graph-processing algorithms on distributed architectures. Université de Technologie de Compiègne
  108. Kai M Ting (2017). Algorithms that Defy the Gravity of Learning Curve. FEDERATION UNIVERSITY AUSTRALIA MOUNT HELEN Australia
  109. Loïc Prieur-Drevon (2017). Structures de données hautement extensibles pour le stockage sur disque de séries temporelles hétérogènes. École Polytechnique de Montréal
  110. Miguel Guagliano, Julián Tornillo, Guadalupe Pascal, Lucas Carroso, and Juan Santiago Pavlicevic (2017). Aplicación de herramientas de vigilancia tecnológica para el relevamiento de tecnologías de código abierto aplicables en la enseñanza de la Ingeniería. XII Congreso de Tecnología en Educación y Educación en Tecnología (TE&ET, La Matanza 2017).
  111. Pallam Anusha, and G.Krishna Reddy (2017). Repeal Adjacent Neighbors In Untrue Interval Base Discovery System. IJITR 5(1), 5552-5554
  112. Paulo Sergio da Conceição Moreira (2017). Mineração de dados aplicada à classificação automática de gêneros musicais.
  113. Renzo Paranaíba Mesquita (2017). Aprimoramentos da Junção Canalizada aplicada em dados Métricos e Espaciais.
  114. Ricardo de Souza Jacomini (2017). Inferência de redes gênicas por agrupamento, busca exaustiva e análise de predição intrinsecamente multivariada. Biblioteca Digital de Teses e Dissertações da Universidade de São Paulo
  115. Rocío Hubert (2017). Análisis y visualización de peticiones, quejas y reclamos ciudadanos. XX Concurso de Trabajos Estudiantiles - JAIIO 46 (Córdoba, 2017).
  116. Réris Aparecida Pereira de Lima (2017). Mineração de dados abertos com a ferramenta weka: microdados CAGED de pessoas com deficiência da Região Sul do Brasil.
  117. Soongeol Kwon (2017). Demand-Side Management for Energy-efficient Data Center Operations with Renewable Energy and Demand Response.
  118. Subscribers Only (2017). A Hierarchical Uncertain Clustering Method for Multi-Relational Data with Incomplete Information. Boletín Técnico, ISSN:0376-723X 55(3)
  119. Thiago Orion Simões Amorim (2017). Bioacústica de baleias cachalotes (Physeter macrocephalus Linnaeus, 1758) com ênfase no oceano Atlântico Sul ocidental. Universidade Federal de Juiz de Fora (UFJF)
  120. Vanessa Estefania Quintana Bajaña, and Sandro Anibal Yagual Tomala (2017). Propuesta de Aplicación Predictiva de Aprobación de una Asignatura con Flujo Previo a Través de Algoritmos Basados en Software WEKA Para Estudiantes del Ultimo Semestre de la Carrera de Ingeniería en Sistemas Computacionales de la Universidad de Guayaquil. Universidad de Guayaquil. Facultad de Ciencias Matematicas y Fisicas. Carrera de Ingenieria en Sistemas Computacionales
  121. Yu-Wei Liao (2017). 使用權重動態視窗之密度導向的局部離群值偵測演算法. 中興大學資訊科學與工程學系學位論文, 1-55, 中興大學
  122. Гущина Оксана Александровна (2017). Применение интеллектуальных систем при управлении рисками программных проектов. Вестник Мордовского университета 27(2), Федеральное государственное бюджетное образовательное учреждение высшего образования «Национальный исследовательский Мордовский государственный университет им. Н. П. Огарёва»
  123. Малютин Евгений Алексеевич, Бугайченко Дмитрий Юрьевич, and Мишенин Алексей Николаевич (2017). Выделение текстовых трендов в социальной сети ok. Вестник Санкт-Петербургского университета. Серия 10. Прикладная математика. Информатика. Процессы управления, Федеральное государственное бюджетное образовательное учреждение высшего образования «Санкт-Петербургский государственный университет»
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2016

  1. Joy Mustafi (2016). Natural Language Processing and Machine Learning for Big Data. Techniques and Environments for Big Data Analysis, 53-74, Springer, 10.1007/978-3-319-27520-8_4
  2. Johannes Blömer, and Kathrin Bujna (2016). Adaptive Seeding for Gaussian Mixture Models. PAKDD (2), 296-308, Springer, 10.1007/978-3-319-31750-2_24, BibTeX
  3. Amin Aghaee, Mehrdad Ghadiri, and Mahdieh Soleymani Baghshah (2016). Active Distance-Based Clustering Using K-Medoids. PAKDD (1), 253-264, Springer, 10.1007/978-3-319-31753-3_21, BibTeX
  4. Smita Chormunge, and Sudarson Jena (2016). Performance Efficiency and Effectiveness of Clustering Methods for Microarray Datasets. Smart Innovation, Systems and Technologies, 557-567, Springer, 10.1007/978-81-322-2529-4_58
  5. Guilherme Oliveira Campos, Arthur Zimek, Jörg Sander, Ricardo J. G. B. Campello, Barbora Micenková, Erich Schubert, Ira Assent, and Michael E. Houle (2016). On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study. Data Min. Knowl. Discov. 30(4), 891-927, 10.1007/s10618-015-0444-8, BibTeX
  6. Bo Jiang, Feiyue Qiu, and Liping Wang (2016). Multi-view clustering via simultaneous weighting on views and features. Appl. Soft Comput. 47, 304-315, 10.1016/j.asoc.2016.06.010, BibTeX
  7. Manal T. Adham, and Peter J. Bentley (2016). Evaluating clustering methods within the Artificial Ecosystem Algorithm and their application to bike redistribution in London. Biosyst. 146, 43-59, 10.1016/j.biosystems.2016.04.008, BibTeX
  8. Felix Stahlberg, Tim Schlippe, Stephan Vogel, and Tanja Schultz (2016). Word segmentation and pronunciation extraction from phoneme sequences through cross-lingual word-to-phoneme alignment. Comput. Speech Lang. 35, 234-261, 10.1016/j.csl.2014.10.001, BibTeX
  9. Bo Jiang, Feiyue Qiu, Liping Wang, and Zhenjun Zhang (2016). Bi-level weighted multi-view clustering via hybrid particle swarm optimization. Inf. Process. Manag. 52(3), 387-398, 10.1016/j.ipm.2015.11.003, BibTeX
  10. Piotr Przybyla, Matthew Shardlow, Sophie Aubin, Robert Bossy, Richard Eckart de Castilho, Stelios Piperidis, John McNaught, and Sophia Ananiadou (2016). Text mining resources for the life sciences. Database J. Biol. Databases Curation 2016, 10.1093/database/baw145, BibTeX
  11. Shane Gero, Hal Whitehead, and Luke Rendell (2016). Individual, unit and vocal clan level identity cues in sperm whale codas. Royal Society Open Science 3(1), 150372, The Royal Society, 10.1098/rsos.150372
  12. Shane Gero, Anne Bøttcher, Hal Whitehead, and Peter Teglberg Madsen (2016). Socially segregated, sympatric sperm whale clans in the Atlantic Ocean. Royal Society Open Science 3(6), 160061, The Royal Society, 10.1098/rsos.160061
  13. Bo Jiang, Feiyue Qiu, Shipin Yang, and Liping Wang (2016). Evolutionary multi-objective optimization for multi-view clustering. CEC, 3308-3315, IEEE, 10.1109/CEC.2016.7744208, BibTeX
  14. Wei Ye, Samuel Maurus, Nina Hubig, and Claudia Plant (2016). Generalized Independent Subspace Clustering. ICDM, 569-578, IEEE, 10.1109/ICDM.2016.0068, BibTeX
  15. Dominik Mautz, Christian Böhm, and Claudia Plant (2016). Subspace Clustering Ensembles through Tensor Decomposition. ICDM Workshops, 1225-1234, IEEE, 10.1109/ICDMW.2016.0177, BibTeX
  16. Martin Jenckel, Syed Saqib Bukhari, and Andreas Dengel (2016). anyOCR: A sequence learning based OCR system for unlabeled historical documents. ICPR, 4035-4040, IEEE, 10.1109/ICPR.2016.7900265, BibTeX
  17. Xu Han, Chee Keong Kwoh, and Jung-jae Kim (2016). Clustering based active learning for biomedical Named Entity Recognition. IJCNN, 1253-1260, IEEE, 10.1109/IJCNN.2016.7727341, BibTeX
  18. Vinh Truong Hoang, Alice Porebski, Nicolas Vandenbroucke, and Denis Hamad (2016). LBP parameter tuning for texture analysis of lace images. IPAS, 1-6, IEEE, 10.1109/IPAS.2016.7880063, BibTeX
  19. Josua Krause, Aritra Dasgupta, Jean-Daniel Fekete, and Enrico Bertini (2016). SeekAView: An intelligent dimensionality reduction strategy for navigating high-dimensional data spaces. LDAV, 11-19, IEEE, 10.1109/LDAV.2016.7874305, BibTeX
  20. Venkatesh Kulkarni, and Manju Nanda (2016). Data driven prognosis approach for safety critical systems. 2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), 1699-1703, IEEE, 10.1109/RTEICT.2016.7808123
  21. MingJie Tang, Ruby Y. Tahboub, Walid G. Aref, Mikhail J. Atallah, Qutaibah M. Malluhi, Mourad Ouzzani, and Yasin N. Silva (2016). Similarity Group-by Operators for Multi-Dimensional Relational Data. IEEE Trans. Knowl. Data Eng. 28(2), 510-523, 10.1109/TKDE.2015.2480400, BibTeX
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  49. Johannes Schneider, and Thomas Locher (2016). Obfuscation using Encryption. CoRR abs/1612.03345, BibTeX
  50. Klaus Arthur Schmid (2016). Searching and mining in enriched geo-spatial data. Ludwig Maximilian University of Munich, Germany, BibTeX
  51. Michael Weiler (2016). Event detection in high throughput social media. Ludwig Maximilian University of Munich, Germany, BibTeX
  52. Simon Maag, and Hanspeter Kriesi (2016). Politicisation, conflicts and the structuring of the EU political space. Politicising Europe, Cambridge University Press, 9781107129412
  53. Ahmed Balfagih (2016). Direct Selling Business Lead Prediction by Social Media Data Mining.
  54. Alexander Fischer-Brandies (2016). Explaining Outliers in ARTigo. Ludwig-Maximilians-Universität München
  55. Anthony McCaffrey, and University Of Massachusetts (2016). Feature type spectrum technique.
  56. B. Gajewski, and T. Martyn (2016). Spatial data clustering in independent mobile environment. Measurement Automation Monitoring Vol. 62, No. 5
  57. Bruno Miguel Nunes da Silva (2016). Exploratory Cluster Analysis from Ubiquitous Data Streams using Self-Organizing Maps.
  58. Christopher Håkansson (2016). Clustering driver’s destinations - using internal evaluation to adaptively set parameters.
  59. Francisco Daniel Porras Bernárdez (2016). Extraction of User’s Stays and Transitions from GPS Logs: A Comparison of Three Spatio-Temporal Clustering Approaches.
  60. Frederic Sautter (2016). Association Rule Generation and Evaluation of Interestingness Measures for Artwork Tags. Ludwig-Maximilians-Universität München
  61. G. O. Campos, A. Zimek, J. Sander, R. J. G. B. Campello, B. Micenková, E. Schubert, I. Assent, and M. E. Houle (2016). On the Evaluation of Outlier Detection: Measures, Datasets, and an Empirical Study Continued. Proceedings of the LWDA 2016 Workshops: KDML, FGWM, FGIR, and FGDB, Potsdam, Germany
  62. Helmut Neukirchen (2016). Survey and Performance Evaluation of DBSCAN Spatial Clustering Implementations for Big Data and High-Performance Computing Paradigms. Technical report VHI-01-2016, Engineering Research Institute, University of Iceland
  63. Hrvoje Brlečić Layer (2016). Klasifikacija energetskih subjekata u Republici Hrvatskoj korištenjem otkrivanja znanja iz baza podataka. University of Zagreb. Faculty of Economics and Business.
  64. Huang Dan (2016). Design and implementation of semantic annotation system based on fragmentation knowledge. E.T.S. de Ingenieros Informáticos (UPM)
  65. Jakub Velkoborský (2016). Hierarchical visualization of the chemical space.
  66. Jeffrey Hudack (2016). Risk-Aware Planning for Sensor Data Collection. Syracuse University
  67. Joonas Puura (2016). Tarkvara loomine erinevate k-keskmiste algoritmide rakendamiseks (Software for Clustering Using k-means Algorithms).
  68. Justin Sam Chew, and Maurice HT Ling (2016). TAPPS Release 1: Plugin-Extensible Platform for Technical Analysis and Applied Statistics. Advances in Computer Science: an International Journal 5(1), 132-141
  69. Laleh Jalali (2016). Interactive Event-driven Knowledge Discovery from Data Streams. UC Irvine
  70. Luca Putelli (2016). Estrazione di regole di associazione da dati RDF. Italy
  71. Martin Jenckel, Syed Saqib Bukhari, and Andreas Dengel (2016). Clustering Benchmark for Characters in Historical Documents. DAS 2016 Short Paper Booklet, 33-34
  72. Miguel José Cavadas Santos (2016). Automated Scalable Platform for Packet Traffic Analysis.
  73. Mingjie Tang (2016). Efficient processing of similarity queries with applications. Purdue University
  74. Mustafa Takaoğlu (2016). Birkaç Veri Kümesi ile WEKA ve MATLAB Üzerinde Kümeleme Algoritmalarının Karşılaştırılarak İncelenmesi. İstanbul Aydin Üni̇versi̇tesi̇ Fen Bi̇li̇mleri̇ Ensti̇tüsü
  75. N. Srujana, G. Srinivasa Rao, and M. V. Sivaprasad (2016). Unsupervised Distance-Based Outlier Detection In High Dimensional Data. IJITR 4(5), 3905–3907
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2015

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  63. Toon van Craenendonck, and Hendrik Blockeel (2015). Limitations of Using Constraint Set Utility in Semi-Supervised Clustering. MetaSel@PKDD/ECML, 27-42, CEUR-WS.org, BibTeX
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  65. Keqian Li (2015). On Integrating Information Visualization Techniques into Data Mining: A Review. CoRR abs/1503.00202, BibTeX
  66. Johannes Niedermayer (2015). Complex queries and complex data: challenges in similarity search. Ludwig Maximilians University Munich, BibTeX
  67. Matthias Rohr (2015). Workload-sensitive Timing Behavior Analysis for Fault Localization in Software Systems. University of Kiel, BibTeX
  68. Julien Soler (2015). Orion, A Generic Model for Data Mining: Application to Video Games. (Orion, un modèle générique pour la fouille de données: application aux jeux vidéo). University of Western Brittany, Brest, France, BibTeX
  69. Akshay Vishwanath Bhinge (2015). A comparative study on data mining tools.
  70. Barbora Micenková (2015). Outlier Detection and Explanation for Domain Experts. Department of Computer Science, University of Aarhus
  71. Bryan Omar Collazo Santiago (2015). Machine learning blocks. Massachusetts Institute of Technology
  72. Carl Levin, and Christopher Håkansson (2015). Clustering driver’s destinations - using internal evaluation to adaptively set parameters.
  73. Gilad Armon, Adiel Loinger, Uri Blatt, and Shahar Siegman (2015). Benchmarking In Online Advertising.
  74. Gordon O Ondego (2015). A comparative study of decision Tree and Naïve Bayesian Classifiers on Verbal Autopsy Datasets. University of Nairobi
  75. I Gusti Bagus Ady Sutrisna, Kemas Rahmat Saleh Wiharja, and Alfian Akbar Gozali (2015). Penerapan Algoritma GRAC (Graph Algorithm Clustering) untuk Graph Database Compression). eProceedings of Engineering 2(1)
  76. Irene Fernández Sánchez (2015). Diseño de una metodología de evaluación de servicios públicos basada en modelos analíticos sobre datos abiertos y de redes sociales. Telecomunicacion
  77. Jonathan von Brünken, Michael E. Houle, and Arthur Zimek (2015). Intrinsic Dimensional Outlier Detection in High-Dimensional Data. NII Technical Report (NII-2015-003E), NII
  78. Judit Kockat, and Clemens Rohde (2015). Conditions for local adaption of building policies in German cities according to their building structure and demography. ECEEE
  79. Katarzyna Racka (2015). Metody eksploracji danych i ich zastosowanie. Zeszyty Naukowe Państwowej Wyższej Szkoły Zawodowej w Płocku. Nauki Ekonomiczne 21 Wybrane problemy gospodarki europejskiej, 143-150
  80. Konstantinos Kontakis, and Κωνσταντίνος Κοντάκης (2015). Σημασιολογική περιγραφή σκηνών σε περιβάλλοντα εικονικής πραγματικότητας. Τ.Ε.Ι. Κρήτης, Σχολή Τεχνολογικών Εφαρμογών (Σ.Τ.Εφ), ΠΜΣ Πληροφορική και Πολυμέσα
  81. Křeček Martin (2015). Rozšíření platformy Clueminer o grafové algoritmy. České vysoké učení technické v Praze. Vypočetní a informační centrum.
  82. Lasanthi Nilmini Heendaliya (2015). Enabling near-term prediction of status for intelligent transportation systems: Management techniques for data on mobile objects. Missouri University of Science and Technology
  83. Lev Aleksandrovich Kazakovtsev, Aljona Aleksandrovna Stupina, Victor Ivanovich Orlov, Margarita Vladimirovna Karaseva, and Igor Sergeevich Masich (2015). Clustering Methods For Classification Of Electronic Devices By Production Batches And Quality Classes. Facta Universitatis, Series: Mathematics and Informatics 30(5), 567-581
  84. Lev Aleksandrovich Kazakovtsev, Victor Orlov, Aljona Aleksandrovna Stupina, and Vladimir Kazakovtsev (2015). Modied Genetic Algorithm with Greedy Heuristic for Continuous and Discrete p-Median Problems. Facta Universitatis, Series: Mathematics and Informatics 30(1), 89-106
  85. Mansi Gera (2015). An Approach for Improving Accuracy of Prediction Using Ensemble Modeling.
  86. Markku Silén (2015). Symbolisen ja numeerisen laskennan ohjelmat opiskelijan apuna. Lapin ammattikorkeakoulu
  87. Monika Kofler (2015). Optimising the storage location assignment problem under dynamic conditions.
  88. Preeti Bhargava (2015). Towards Proactive Context-aware Computing and Systems.
  89. Rashedul Amin Tuhin (2015). Securing GNSS Receivers with a Density-based Clustering Algorithm.
  90. Swetha Rajendiran (2015). Learning classification algorithms in data mining.
  91. Tharindu R. Bandaragoda (2015). Isolation based anomaly detection: a re-examination. Monash University
  92. Yan Liao, Jialin Hua, and Wensheng Zhu (2015). An Effective Divide-and-Merge Method for Hierarchical Clustering. American Scientific Publishers
  93. Zoltan Geler (2015). Role of Similarity Measures in Time Series Analysis. Универзитет у Новом Саду, Природно-математички факултет
  94. Zoraida Emperatriz Mamani Rodríguez (2015). Aplicación de la minería de datos distribuida usando algoritmo de clustering k-means para mejorar la calidad de servicios de las organizaciones modernas caso: Poder judicial. Universidad Nacional Mayor de San Marcos. Programa Cybertesis PERÚ
  95. Δημήτριος Νικηφοράκης (2015). Ομαδοποίηση γράφων με τους αλγόριθμους k-means και DBSCAN.
  96. Л.А. Казаковцев, А.А. Ступина, and В.И. Орлов (2015). Выбор Метрики Для Системы Автоматической Классификации Электрорадиоизделий По Производственным Партиям. Программные продукты и системы, Закрытое акционерное общество Научно-исследовательский институт “Центрпрограммсистем”
  97. 신동화, 이세희, and 서진욱 (2015). 계층 발생 프레임워크를 이용한 군집 계층 시각화. 정보과학회 컴퓨팅의 실제 논문지 21(6), 436-441

2014

  1. Maria Camila Nardini Barioni, Humberto Luiz Razente, Alessandra M. R. Marcelino, Agma J. M. Traina, and Caetano Traina Jr. (2014). Open issues for partitioning clustering methods: an overview. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 4(3), 161-177, 10.1002/widm.1127, BibTeX
  2. Mathilde Sahuguet, and Benoit Huet (2014). Mining the Web for Multimedia-Based Enriching. MMM (2), 263-274, Springer, 10.1007/978-3-319-04117-9_24, BibTeX
  3. Neil Scicluna, and Christos-Savvas Bouganis (2014). FPGA-Based Parallel DBSCAN Architecture. ARC, 1-12, Springer, 10.1007/978-3-319-05960-0_1, BibTeX
  4. Mahsa Salehi, Christopher A. Leckie, Masud Moshtaghi, and Tharshan Vaithianathan (2014). A Relevance Weighted Ensemble Model for Anomaly Detection in Switching Data Streams. PAKDD (2), 461-473, Springer, 10.1007/978-3-319-06605-9_38, BibTeX
  5. Sunil Aryal, Kai Ming Ting, Jonathan R. Wells, and Takashi Washio (2014). Improving iForest with Relative Mass. PAKDD (2), 510-521, Springer, 10.1007/978-3-319-06605-9_42, BibTeX
  6. Giuseppe Rizzo, Giacomo Falcone, Rosa Meo, Ruggero G. Pensa, Raphaël Troncy, and Vuk Milicic (2014). Geographic Summaries from Crowdsourced Data. ESWC (Satellite Events), 477-482, Springer, 10.1007/978-3-319-11955-7_70, BibTeX
  7. Johannes Niedermayer, and Peer Kröger (2014). Retrieval of Binary Features in Image Databases: A Study. SISAP, 151-163, Springer, 10.1007/978-3-319-11988-5_14, BibTeX
  8. Kirill Smirnov, George A. Chernishev, Pavel Fedotovsky, George Erokhin, and Kirill Cherednik (2014). The Study of Multidimensional R-Tree-Based Index Scalability in Multicore Environment. Ershov Memorial Conference, 266-272, Springer, 10.1007/978-3-662-46823-4_22, BibTeX
  9. Jeremy Steinhauer, Lois M. L. Delcambre, Marianne Lykke, and Marit Kristine Ådland (2014). Evaluating distance-based clustering for user (browse and click) sessions in a domain-specific collection. Int. J. Digit. Libr. 14(3-4), 167-179, 10.1007/s00799-014-0117-z, BibTeX
  10. Erich Schubert, Arthur Zimek, and Hans-Peter Kriegel (2014). Local outlier detection reconsidered: a generalized view on locality with applications to spatial, video, and network outlier detection. Data Min. Knowl. Discov. 28(1), 190-237, 10.1007/s10618-012-0300-z, BibTeX
  11. Michael Davis, Weiru Liu, and Paul C. Miller (2014). Finding the most descriptive substructures in graphs with discrete and numeric labels. J. Intell. Inf. Syst. 42(2), 307-332, 10.1007/978-3-642-37382-4_10, BibTeX
  12. Chen Lin, Runquan Xie, Xinjun Guan, Lei Li, and Tao Li (2014). Personalized news recommendation via implicit social experts. Inf. Sci. 254, 1-18, 10.1016/j.ins.2013.08.034, BibTeX
  13. Jonathan R. Wells, Kai Ming Ting, and Takashi Washio (2014). LiNearN: A new approach to nearest neighbour density estimator. Pattern Recognit. 47(8), 2702-2720, 10.1016/j.patcog.2014.01.013, BibTeX
  14. Allison Reilly, and Seth Guikema (2014). Bayesian Multiscale Modeling of Spatial Infrastructure Performance Predictions with an Application to Electric Power Outage Forecasting. J. Infrastruct. Syst., 04014036, American Society of Civil Engineers (ASCE), 10.1061/(ASCE)IS.1943-555X.0000222
  15. Hua Lou, and Ye Zhu (2014). Bivariate probability-based anomaly detection. BESC, 81-86, IEEE, 10.1109/BESC.2014.7059512, BibTeX
  16. Francesco Alex Indaco, and Teng-Sheng Moh (2014). Hierarchical Density-Based Clustering Using Level-Sets. CloudCom, 692-695, IEEE, 10.1109/CloudCom.2014.126, BibTeX
  17. Xuan-Hong Dang, Ira Assent, Raymond T. Ng, Arthur Zimek, and Erich Schubert (2014). Discriminative features for identifying and interpreting outliers. ICDE, 88-99, IEEE, 10.1109/ICDE.2014.6816642, BibTeX
  18. Tharindu R. Bandaragoda, Kai Ming Ting, David W. Albrecht, Fei Tony Liu, and Jonathan R. Wells (2014). Efficient Anomaly Detection by Isolation Using Nearest Neighbour Ensemble. ICDM Workshops, 698-705, IEEE, 10.1109/ICDMW.2014.70, BibTeX
  19. Tamer F. Ghanem, Wail S. Elkilani, Hatem S. Ahmed, and Mohiy M. Hadhoud (2014). DPM: Fast and scalable clustering algorithm for large scale high dimensional datasets. 2014 10th International Computer Engineering Conference (ICENCO), 26-35, IEEE, 10.1109/ICENCO.2014.7050427
  20. Johannes Blömer, Kathrin Bujna, and Daniel Kuntze (2014). A Theoretical and Experimental Comparison of the EM and SEM Algorithm. ICPR, 1419-1424, IEEE, 10.1109/ICPR.2014.253, BibTeX
  21. Alan Jovic, Karla Brkic, and Nikola Bogunovic (2014). An overview of free software tools for general data mining. MIPRO, 1112-1117, IEEE, 10.1109/MIPRO.2014.6859735, BibTeX
  22. Veit Köppen, Martin Schäler, and Reimar Schröter (2014). Toward variability management to tailor high dimensional index implementations. RCIS, 1-6, IEEE, 10.1109/RCIS.2014.6861069, BibTeX
  23. Erich Schubert, Arthur Zimek, and Hans-Peter Kriegel (2014). Generalized Outlier Detection with Flexible Kernel Density Estimates. SDM, 542-550, SIAM, 10.1137/1.9781611973440.63, BibTeX
  24. Mohamed Bouguessa (2014). A Mixture Model-Based Combination Approach for Outlier Detection. Int. J. Artif. Intell. Tools 23(4), 10.1142/S0218213014600215, BibTeX
  25. Arthur Zimek, Ricardo J. G. B. Campello, and Jörg Sander (2014). Data perturbation for outlier detection ensembles. SSDBM, 13:1-13:12, ACM, 10.1145/2618243.2618257, BibTeX
  26. Xiao He, Jing Feng, Bettina Konte, Son T. Mai, and Claudia Plant (2014). Relevant overlapping subspace clusters on categorical data. KDD, 213-222, ACM, 10.1145/2623330.2623652, BibTeX
  27. Andreas Züfle, Tobias Emrich, Klaus Arthur Schmid, Nikos Mamoulis, Arthur Zimek, and Matthias Renz (2014). Representative clustering of uncertain data. KDD, 243-252, ACM, 10.1145/2623330.2623725, BibTeX
  28. Erich Schubert, Michael Weiler, and Hans-Peter Kriegel (2014). SigniTrend: scalable detection of emerging topics in textual streams by hashed significance thresholds. KDD, 871-880, ACM, 10.1145/2623330.2623740, BibTeX
  29. Dominique Legallois, Solen Quiniou, Peggy Cellier, and Thierry Charnois (2014). Graph Mining under Linguistic Constraints for Exploring Large Texts. Instituto Politécnico Nacional, 10.13053/cys-17-2-1529
  30. Shaobin Huang, Yuan Cheng, Dapeng Lang, Ronghua Chi, and Guofeng Liu (2014). A Formal Algorithm for Verifying the Validity of Clustering Results Based on Model Checking. PLoS ONE 9(3), e90109, Public Library of Science (PLoS), 10.1371/journal.pone.0090109
  31. Reka K. Kelemen, Gengen F. He, Hannah L. Woo, Thomas Lane, Caroline Rempe, Jun Wang, Ian A. Cockburn, Rogerio Amino, Vitaly V. Ganusov, and Michael W. Berry (2014). Classification of T cell movement tracks allows for prediction of cell function. Int. J. Comput. Biol. Drug Des. 7(2/3), 113-129, 10.1504/IJCBDD.2014.061655, BibTeX
  32. Tim Zwietasch (2014). Detecting anomalies in system log files using machine learning techniques. Uni Stuttgart - Universitätsbibliothek, 10.18419/opus-3454
  33. Deborah Falcone, Cecilia Mascolo, Carmela Comito, Domenico Talia, and Jon Crowcroft (2014). What is this place? Inferring place categories through user patterns identification in geo-tagged tweets. MobiCASE, 10-19, IEEE, 10.4108/icst.mobicase.2014.257683, BibTeX
  34. A. Mehta, and O. Dikshit (2014). SPCA Assisted Correlation Clustering of Hyperspectral Imagery. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-8, 111-116, Copernicus GmbH, 10.5194/isprsannals-II-8-111-2014
  35. Mojgan Pourrajabi, Davoud Moulavi, Ricardo J. G. B. Campello, Arthur Zimek, Jörg Sander, and Randy Goebel (2014). Model Selection for Semi-Supervised Clustering. EDBT, 331-342, OpenProceedings.org, 10.5441/002/edbt.2014.31, BibTeX
  36. Felix Stahlberg, Tim Schlippe, Stephan Vogel, and Tanja Schultz (2014). Towards automatic speech recognition without pronunciation dictionary, transcribed speech and text resources in the target language using cross-lingual word-to-phoneme alignment. SLTU, 73-80, ISCA, BibTeX
  37. Stephan Günnemann, Hardy Kremer, Matthias Hannen, and Thomas Seidl (2014). KDD-SC: Subspace Clustering Extensions for Knowledge Discovery Frameworks. CoRR abs/1407.3850, BibTeX
  38. Albrecht Zimmermann (2014). A feature construction framework based on outlier detection and discriminative pattern mining. CoRR abs/1407.4668, BibTeX
  39. Xiao He (2014). Multi-purpose exploratory mining of complex data. Ludwig Maximilians University Munich, Germany, BibTeX
  40. Richard Röttger (2014). Active transitivity clustering of large-scale biomedical datasets. Saarland University, BibTeX
  41. Michael Davis (2014). Discovering patterns and anomalies in graphs with discrete and numeric attributes. Queen’s University Belfast, UK, BibTeX
  42. Ibrahim Mithgal Aljarah (2014). MapReduce-enabled scalable nature-inspired approaches for clustering. North Dakota State University, 978-1-303-83676-3
  43. Samuel Valentine (2014). Sentiment Analysis 19 Success Secrets - 19 Most Asked Questions On Sentiment Analysis - What You Need To Know. Emereo Publishing, 9781488535208
  44. Adnan Karaibrahimoğlu (2014). Veri madenciliğinden birliktelik kuralı ile onkoloji verilerinin analiz edilmesi: Meram Tıp Fakültesi Onkoloji örneği (Analyzing breast cancer data using association rule mining: Meram Faculty of Medicine Oncology Department). Selçuk Üniversitesi Fen Bilimleri Enstitüsü
  45. Andrea Bagnacani (2014). Linked Data e bibliometriche: un indice di multidisciplinarieta nel Semantic Publishing.
  46. Björn Löfroth (2014). Mobile traffic dataset comparisons throughcluster analysis of radio network event sequences.
  47. Borut Sluban (2014). Ensemble-Based Noise And Outlier Detection. Jožef Stefan International Postgraduate School
  48. Ektabahen Kanubhai Patel (2014). A web based data mining courseware.
  49. Florian Hoidn (2014). The Analytics Center: Devising a Citizen Science Data Mining Tool for the ARTigo Image Tagging Project. Ludwig-Maximilians-Universität München
  50. Haofan Zhang (2014). Spectral Ranking and Unsupervised Feature Selection for Point, Collective and Contextual Anomaly Detection.
  51. Henrik Larsson, and Erik Lindqvist (2014). Unsupervised Outlier Detection in Software Engineering. Institutionen för data- och informationsteknik (Chalmers), Chalmers tekniska högskola
  52. Jichao Sun (2014). Local selection of features and its applications to image search and annotation. New Jersey Institute of Technology
  53. João Luiz Grave Gross (2014). URSA: um framework para agrupamento de dados e validação de resultados (URSA: a framework for data clustering and data analysis).
  54. Kaisa Vent (2014). Inimese tegevuskohtade leidmine nutitelefonipõhiste käitumisandmestike alusel. Tartu Ülikool
  55. Milan. Vukićević (2014). Razvoj i projektovanje algoritama za klasterovanje ekspresija gena (Development and design of algorithms for clustering gene expression data: doctoral dissertation). Univerzitet u Beogradu, Fakultet organizacionih nauka
  56. Muhammad Sohail (2014). Calculation of Energy Footprint of Manufacturing Assets.
  57. Nicola Padovano, and Elia Filiberto Polo (2014). Progetto e realizzazione di un framework per Neosperience sul clustering di reti sociali. Italy
  58. Pratik Kumar Mishra, Dinesh Pothineni, Aadil Rasheed, Deepak Sundararajan, Ashok Krish, Hasit Kaji, and Tata Consultancy Services Limited (2014). System and Method for Determining an Expert of a Subject on a Web-based Platform.
  59. R.J. Ma, and N.Y. Yu (2014). A new route for energy efficiency diagnosis and potential analysis of energy consumption from air-conditioning system. Energy Systems Laboratory (http://esl.tamu.edu)
  60. Reka Katalin Kelemen (2014). Mathematical modeling of T cell clustering following malaria infection in mice. University of Tennessee, Knoxville
  61. Ritesh Shukla (2014). Machine learning ecosystem: implications for business strategy centered on machine learning. Massachusetts Institute of Technology
  62. Robert F Erbacher, and Robinson Pino (2014). Open Source Software Tools for Anomaly Detection Analysis. ARL-MR-0869, Army Research Lab Adelphi MD Computational and Information Sciences Directorate
  63. Sheila Mollá Santiago (2014). Generalització de mètodes de density-based clustering a dades mixtes. Universitat Politècnica de Catalunya
  64. Tânia Margarida dos Santos Gomes (2014). Ferramentas open source de Data Mining.
  65. V. Ilango (2014). Forecasting Methods Based on Outlier Detection And Influential Point Observation on Clustering Techniques Using Financial Time Series Data. Virudhunagar
  66. Y.P.J.M. van Oirschot (2014). Using Trace Clustering for Configurable Process Discovery Explained by Event Log Data.
  67. И.А. Пестунов, and С.А. Рылов (2014). Метод построения ансамбля сеточных иерархических алгоритмов кластеризации для сегментации спутниковых изображений. Региональные проблемы дистанционного зондирования Земли, 215-223
  68. Казаковцев Лев Александрович, Орлов Виктор Иванович, Ступина Алена Александровна, and Масич Игорь Сергеевич (2014). Задача классификации электронной компонентной базы. Вестник Сибирского государственного университета науки и технологий имени академика М. Ф. Решетнева, Федеральное государственное бюджетное образовательное учреждение высшего образования «Сибирский государственный университет науки и технологий имени академика М.Ф. Решетнева»

2013

  1. Zeyar Aung (2013). Database Systems for the Smart Grid. Smart Grids, 151-168, Springer, 10.1007/978-1-4471-5210-1_7
  2. Charu C. Aggarwal (2013). Outlier Analysis. Springer, 10.1007/978-1-4614-6396-2, BibTeX
  3. Charu C. Aggarwal (2013). Applications of Outlier Analysis. Outlier Analysis, 373-400, Springer, 10.1007/978-1-4614-6396-2_12
  4. Charu C. Aggarwal (2013). High-Dimensional Outlier Detection: The Subspace Method. Outlier Analysis, 135-167, Springer, 10.1007/978-1-4614-6396-2_5
  5. Jordi Nin, David Carrera, and Daniel Villatoro (2013). On the Use of Social Trajectory-Based Clustering Methods for Public Transport Optimization. CitiSens, 59-70, Springer, 10.1007/978-3-319-04178-0_6, BibTeX
  6. Mark J. Embrechts, Christopher J. Gatti, Jonathan Linton, and Badrinath Roysam (2013). Hierarchical Clustering for Large Data Sets. Advances in Intelligent Signal Processing and Data Mining, 197-233, Springer, 10.1007/978-3-642-28696-4_8
  7. Mariusz Oszust, and Marian Wysocki (2013). Clustering and Classification of Time Series Representing Sign Language Words. ICAISC (2), 218-229, Springer, 10.1007/978-3-642-38610-7_21, BibTeX
  8. Rana Momtaz, Nesma Mohssen, and Mohammad A. Gowayyed (2013). DWOF: A Robust Density-Based Outlier Detection Approach. IbPRIA, 517-525, Springer, 10.1007/978-3-642-38628-2_61, BibTeX
  9. Felix Stahlberg, Tim Schlippe, Stephan Vogel, and Tanja Schultz (2013). Pronunciation Extraction from Phoneme Sequences through Cross-Lingual Word-to-Phoneme Alignment. SLSP, 260-272, Springer, 10.1007/978-3-642-39593-2_23, BibTeX
  10. Tobias Emrich, Hans-Peter Kriegel, Peer Kröger, Johannes Niedermayer, Matthias Renz, and Andreas Züfle (2013). Reverse-k-Nearest-Neighbor Join Processing. SSTD, 277-294, Springer, 10.1007/978-3-642-40235-7_16, BibTeX
  11. Erich Schubert, Arthur Zimek, and Hans-Peter Kriegel (2013). Geodetic Distance Queries on R-Trees for Indexing Geographic Data. SSTD, 146-164, Springer, 10.1007/978-3-642-40235-7_9, BibTeX
  12. Jeremy Steinhauer, Lois M. L. Delcambre, Marianne Lykke, and Marit Kristine Ådland (2013). Do User (Browse and Click) Sessions Relate to Their Questions in a Domain-Specific Collection?. TPDL, 96-107, Springer, 10.1007/978-3-642-40501-3_10, BibTeX
  13. Enikö Székely, Pascal Poncelet, Florent Masseglia, Maguelonne Teisseire, and Renaud Cezar (2013). A Density-Based Backward Approach to Isolate Rare Events in Large-Scale Applications. Discovery Science, 249-264, Springer, 10.1007/978-3-642-40897-7_17, BibTeX
  14. Xuan-Hong Dang, Barbora Micenková, Ira Assent, and Raymond T. Ng (2013). Local Outlier Detection with Interpretation. ECML/PKDD (3), 304-320, Springer, 10.1007/978-3-642-40994-3_20, BibTeX
  15. Part Pramokchon, and Punpiti Piamsa-nga (2013). An Unsupervised, Fast Correlation-Based Filter for Feature Selection for Data Clustering. DaEng, 87-94, Springer, 10.1007/978-981-4585-18-7_10, BibTeX
  16. Christophe Jardin, Arno G. Stefani, Martin Eberhardt, Johannes B. Huber, and Heinrich Sticht (2013). An information-theoretic classification of amino acids for the assessment of interfaces in protein–protein docking. Journal of Molecular Modeling 19(9), 3901-3910, Springer, 10.1007/s00894-013-1916-7
  17. Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Fei Tony Liu, and Sunil Aryal (2013). DEMass: a new density estimator for big data. Knowl. Inf. Syst. 35(3), 493-524, 10.1007/s10115-013-0612-3, BibTeX
  18. Kai Ming Ting, Guang-Tong Zhou, Fei Tony Liu, and Swee Chuan Tan (2013). Mass estimation. Mach. Learn. 90(1), 127-160, 10.1007/s10994-012-5303-x, BibTeX
  19. Ibrahim Aljarah, and Simone A. Ludwig (2013). A new clustering approach based on Glowworm Swarm Optimization. IEEE Congress on Evolutionary Computation, 2642-2649, IEEE, 10.1109/CEC.2013.6557888, BibTeX
  20. Yang Zhao, and Abhishek K. Shrivastava (2013). Combating Sub-Clusters Effect in Imbalanced Classification. ICDM, 1295-1300, IEEE, 10.1109/ICDM.2013.105, BibTeX
  21. Barbora Micenková, Raymond T. Ng, Xuan-Hong Dang, and Ira Assent (2013). Explaining Outliers by Subspace Separability. ICDM, 518-527, IEEE, 10.1109/ICDM.2013.132, BibTeX
  22. Arian Bär, Antonio Paciello, and Peter Romirer-Maierhofer (2013). Trapping botnets by DNS failure graphs: Validation, extension and application to a 3G network. INFOCOM, 3159-3164, IEEE, 10.1109/INFCOM.2013.6567131, BibTeX
  23. Arian Bär, Antonio Paciello, and Peter Romirer-Maierhofer (2013). Trapping botnets by DNS failure graphs: Validation, extension and application to a 3G network. INFOCOM Workshops, 393-398, IEEE, 10.1109/INFCOMW.2013.6562863, BibTeX
  24. Amine Chaibi, Mustapha Lebbah, and Hanane Azzag (2013). A New Visualization of Group-Outliers in Unsupervised Learning. IV, 162-167, IEEE, 10.1109/IV.2013.20, BibTeX
  25. Elke Achtert, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2013). Interactive data mining with 3D-parallel-coordinate-trees. SIGMOD Conference, 1009-1012, ACM, 10.1145/2463676.2463696, BibTeX
  26. Arthur Zimek, Matthew Gaudet, Ricardo J. G. B. Campello, and Jörg Sander (2013). Subsampling for efficient and effective unsupervised outlier detection ensembles. KDD, 428-436, ACM, 10.1145/2487575.2487676, BibTeX
  27. Benjamin Welton, Evan Samanas, and Barton P. Miller (2013). Mr. Scan: extreme scale density-based clustering using a tree-based network of GPGPU nodes. SC, 84:1-84:11, ACM, 10.1145/2503210.2503262, BibTeX
  28. Johannes Schneider, and Michail Vlachos (2013). Fast parameterless density-based clustering via random projections. CIKM, 861-866, ACM, 10.1145/2505515.2505590, BibTeX
  29. Toon De Pessemier, Simon Dooms, and Luc Martens (2013). A food recommender for patients in a care facility. RecSys, 209-212, ACM, 10.1145/2507157.2507198, BibTeX
  30. Solen Quiniou, Peggy Cellier, Thierry Charnois, and Dominique Legallois (2013). Graph Mining under Linguistic Constraints for Exploring Large Texts. Computación y Sistemas 17(2), 239-250, 10.13053/cys-17-2-1529
  31. Charu C. Aggarwal, and Chandan K. Reddy (2013). Educational and Software Resources for Data Clustering. Data Clustering: Algorithms and Applications, 607-616, CRC Press, 10.1201/9781315373515-24, BibTeX
  32. David Ando, Michael Colvin, Michael Rexach, and Ajay Gopinathan (2013). Physical Motif Clustering within Intrinsically Disordered Nucleoporin Sequences Reveals Universal Functional Features. PLoS ONE 8(9), e73831, Public Library of Science (PLoS), 10.1371/journal.pone.0073831
  33. Martin Schäler, Alexander Grebhahn, Reimar Schröter, Sandro Schulze, Veit Köppen, and Gunter Saake (2013). QuEval: Beyond high-dimensional indexing a la carte. Proc. VLDB Endow. 6(14), 1654-1665, 10.14778/2556549.2556551, BibTeX
  34. Kai M. Ting (2013). Second Generation of Mass Estimation. Defense Technical Information Center, 10.21236/ada590623
  35. Martin Behnisch, Gotthard Meinel, Sebastian Tramsen, and Markus Diesselmann (2013). Using quadtree representations in building stock visualization and analysis. Erdkunde 67(2), 151-166, Erdkunde, 10.3112/erdkunde.2013.02.04
  36. Jai PrakashVerma, Bankim Patel, and Atul Patel (2013). Web Mining: Opinion and Feedback Analysis for Educational Institutions. International Journal of Computer Applications 84(6), 17-22, Foundation of Computer Science, 10.5120/14579-2800
  37. Arthur Zimek (2013). Clustering High-Dimensional Data. Data Clustering: Algorithms and Applications, 201-230, BibTeX
  38. Tobias Emrich, Peer Kröger, Johannes Niedermayer, Matthias Renz, and Andreas Züfle (2013). A Mutual Pruning Approach for RkNN Join Processing. BTW, 21-35, GI, BibTeX
  39. Sylvain Dormieu, and Nicolas Labroche (2013). SNOW, un algorithme exploratoire pour le subspace clustering. EGC, 79-84, Hermann-Éditions, BibTeX
  40. Jens Ehlers (2013). Self-Adaptive Performance Monitoring for Component-Based Software Systems. Softwaretechnik-Trends 33(2), BibTeX
  41. Tobias Emrich (2013). Coping with distance and location dependencies in spatial, temporal and uncertain data. Ludwig Maximilians University Munich, BibTeX
  42. Hardy Kremer (2013). Mining and similarity search in temporal databases. RWTH Aachen University, BibTeX
  43. Daniel Kuntze (2013). Practical algorithms for clustering and modeling large data sets: analysis and improvements. 1-130, University of Paderborn, BibTeX
  44. Erich Schubert (2013). Generalized and efficient outlier detection for spatial, temporal, and high-dimensional data mining. 1-262, Ludwig Maximilians University Munich, BibTeX
  45. Andreas Züfle (2013). Similarity search and mining in uncertain spatial and spatio-temporal databases. 1-397, Ludwig Maximilians University Munich, BibTeX
  46. Matthew Orlinski (2013). Neighbour discovery and distributed spatio-temporal cluster detection in pocket switched networks. University of Manchester, UK, BibTeX
  47. Claire Elizabeth Q (2013). Machine learning analysis of the cultural and cross-cultural aspects of beauty in music. Aberystwyth University, UK, BibTeX
  48. Thomas H. Davenport, and Jinho Kim (2013). Keeping Up with the Quants. Your Guide to Understanding and Using Analytics. Harvard Business Press, 9781422187265
  49. Ivanka Menken (2013). Data Mining Guidance - Real World Application, Templates, Documents, and Examples of the use of Data Mining in the Public Domain. Emereo Publishing, 9781486460458
  50. Albrecht Zimmermann (2013). Feature construction based on class outliers. CW Reports
  51. Bruno Daigle (2013). Méthodes bioinformatiques pour l’évaluation de la classification du virus du papillome humain. Université du Québec à Montréal
  52. Curdin Barandun, Stefan Derungs, and Gino Paulaitis (2013). Mixtape: Analyse und Erstellung Ähnlichkeitsanalyse von Musik anhand einer praktischen Implementation. HSR Hochschule für Technik Rapperswil
  53. Jan Vykopal (2013). Flow-based Brute-force Attack Detection in Large and High-speed Networks. Masarykova univerzita, Fakulta informatiky
  54. Jan Vykopal (2013). SimFlow - a similarity-based detection of brute-force attacks.
  55. Luiz O. Carvalho, Thatyana F. P. Seraphim, Caetano Traina Júnior, and Enzo Seraphim (2013). ObInject: a NoODMG Persistence and Indexing Framework for Object Injection. Journal of Information and Data Management 4(3), 220
  56. Manish Gupta (2013). Outlier detection for information networks. University of Illinois at Urbana-Champaign
  57. Maria José Gomes Pedroto (2013). Estimação de Massa em Energia Eólica.
  58. N Ronald (2013). Workers, adventurers, explorers: uncovering activity patterns in Melbourne. Australasian Transport Research Forum (ATRF), 36th, 2013, Brisbane, Queensland, Australia
  59. Solen Quiniou, Peggy Cellier, Thierry Charnois, and Dominique Legallois (2013). Graph Mining under Linguistic Constraints to Explore Large Texts. International Conference on Intelligent Text Processing and Computational Linguistics (CICLing’13)
  60. Stefan Eduard Raposo Alves (2013). Towards improving WEBSOM with multi-word expressions. Faculdade de Ciências e Tecnologia
  61. Vladimír Matejovský (2013). Podpora shlukování webových stránek pomocí link mining. Masarykova univerzita, Fakulta informatiky

2012

  1. Arthur Zimek, Erich Schubert, and Hans-Peter Kriegel (2012). A survey on unsupervised outlier detection in high-dimensional numerical data. Stat. Anal. Data Min. 5(5), 363-387, 10.1002/sam.11161, BibTeX
  2. Hans-Peter Kriegel, Peer Kröger, and Arthur Zimek (2012). Subspace clustering. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 2(4), 351-364, 10.1002/widm.1057, BibTeX
  3. Charu C. Aggarwal (2012). An Introduction to Outlier Analysis. Outlier Analysis, 1-40, Springer, 10.1007/978-1-4614-6396-2_1
  4. Dawn E. Holmes, Jeffrey Tweedale, and Lakhmi C. Jain (2012). Data Mining Techniques in Clustering, Association and Classification. Data Mining: Foundations and Intelligent Paradigms, 1-6, Springer, 10.1007/978-3-642-23166-7_1
  5. Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer, and Jesse Read (2012). Stream Data Mining Using the MOA Framework. DASFAA (2), 309-313, Springer, 10.1007/978-3-642-29035-0_27, BibTeX
  6. Ira Assent, Philipp Kranen, Corinna Baldauf, and Thomas Seidl (2012). AnyOut: Anytime Outlier Detection on Streaming Data. DASFAA (1), 228-242, Springer, 10.1007/978-3-642-29038-1_18, BibTeX
  7. eva Kühn, Alexander Marek, Thomas Scheller, Vesna Sesum-Cavic, Michael Vögler, and Stefan Craß (2012). A Space-Based Generic Pattern for Self-Initiative Load Clustering Agents. COORDINATION, 230-244, Springer, 10.1007/978-3-642-30829-1_16, BibTeX
  8. Emmanuel Müller, Fabian Keller, Sebastian Blanc, and Klemens Böhm (2012). OutRules: A Framework for Outlier Descriptions in Multiple Context Spaces. ECML/PKDD (2), 828-832, Springer, 10.1007/978-3-642-33486-3_57, BibTeX
  9. Mohamed Bouguessa (2012). Modeling Outlier Score Distributions. ADMA, 713-725, Springer, 10.1007/978-3-642-35527-1_59, BibTeX
  10. Michael Davis, Weiru Liu, and Paul C. Miller (2012). Finding the Most Descriptive Substructures in Graphs with Discrete and Numeric Labels. NFMCP, 138-154, Springer, 10.1007/978-3-642-37382-4_10, BibTeX
  11. Boris Delibasic, Milan Vukicevic, Milos Jovanovic, Kathrin Kirchner, Johannes Ruhland, and Milija Suknovic (2012). An architecture for component-based design of representative-based clustering algorithms. Data Knowl. Eng. 75, 78-98, 10.1016/j.datak.2012.03.005, BibTeX
  12. Elke Achtert, Sascha Goldhofer, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2012). Evaluation of Clusterings - Metrics and Visual Support. ICDE, 1285-1288, IEEE, 10.1109/ICDE.2012.128, BibTeX
  13. Hans-Peter Kriegel, Peer Kröger, Erich Schubert, and Arthur Zimek (2012). Outlier Detection in Arbitrarily Oriented Subspaces. ICDM, 379-388, IEEE, 10.1109/ICDM.2012.21, BibTeX
  14. Mohamed Bouguessa (2012). A Probabilistic Combination Approach to Improve Outlier Detection. ICTAI, 666-673, IEEE, 10.1109/ICTAI.2012.95, BibTeX
  15. Monalisa Mandal, and Anirban Mukhopadhyay (2012). Identifying most relevant non-redundant gene markers from gene expression data using PSO-based graph -theoretic approach. 2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing, 374-379, IEEE, 10.1109/PDGC.2012.6449849
  16. Erich Schubert, Remigius Wojdanowski, Arthur Zimek, and Hans-Peter Kriegel (2012). On Evaluation of Outlier Rankings and Outlier Scores. SDM, 1047-1058, SIAM / Omnipress, 10.1137/1.9781611972825.90, BibTeX
  17. Thomas Bernecker, Franz Graf, Hans-Peter Kriegel, Nepomuk Seiler, Christoph Türmer, and Dieter Dill (2012). Knowing: a generic data analysis application. EDBT, 630-633, ACM, 10.1145/2247596.2247683, BibTeX
  18. Stephan Günnemann, Ines Färber, Kittipat Virochsiri, and Thomas Seidl (2012). Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data. KDD, 352-360, ACM, 10.1145/2339530.2339588, BibTeX
  19. Linda Dib, and Alessandra Carbone (2012). CLAG: an unsupervised non hierarchical clustering algorithm handling biological data. BMC Bioinform. 13, 194, 10.1186/1471-2105-13-194, BibTeX
  20. Thomas Bernecker (2012). Similarity processing in multi-observation data. 1-253, Ludwig Maximilian University of Munich, Germany, BibTeX
  21. Jens Ehlers (2012). Self-adaptive performance monitoring for component-based software systems. 1-232, University of Kiel, BibTeX
  22. Franz Graf (2012). Data and knowledge engineering for medical image and sensor data. 1-221, Ludwig Maximilian University of Munich, Germany, BibTeX
  23. Stephan Günnemann (2012). Subspace clustering for complex data. RWTH Aachen University, BibTeX
  24. Steffen Suchandt, and Hartmut Runge (2012). Along-track interferometry using TanDEM-X: First results from marine and land applications. EUSAR 2012; 9th European Conference on Synthetic Aperture Radar, 392-395, VDE, 978-3-8007-3404-7
  25. Arthur Zimek (2012). There and Back Again Outlier Detection between Statistical Reasoning and Efficient Database Methods.
  26. Bruno Tavares (2012). Sistema de recomendação para plataformas de e-learning. Instituto Politécnico do Porto. Instituto Superior de Engenharia do Porto
  27. E. B. Beuschau (2012). Learning usage behavior based on app feedback.
  28. Francesco Indaco (2012). Hierarchical Clustering Using Level Sets. San Jose State University
  29. Ilango Velchamy, R Subramanian, and V Vasudevan (2012). A Five Step Procedure for Outlier Analysis in Data Mining. European Journal of Scientific Research
  30. Γρηγόριος Αθανασίου (2012). Business plan νέας ηλεκτρονικής επιχείρησης (Δημιουργία-Εφαρμογή). Πανεπιστήμιο Μακεδονίας Οικονομικών και Κοινωνικών Επιστημών
  31. Νικόλαος Δ. Γρίβας, and Nikolaos D. Grivas (2012). Υπολογισμός ισοχρονικών καμπύλων χρονοαπόστασης σε οδικά δίκτυα (Isochrone computation on road networks).

2011

  1. Hans-Peter Kriegel, Peer Kröger, Jörg Sander, and Arthur Zimek (2011). Density-based clustering. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 1(3), 231-240, 10.1002/widm.30, BibTeX
  2. Thomas Bernecker, Michael E. Houle, Hans-Peter Kriegel, Peer Kröger, Matthias Renz, Erich Schubert, and Arthur Zimek (2011). Quality of Similarity Rankings in Time Series. SSTD, 422-440, Springer, 10.1007/978-3-642-22922-0_25, BibTeX
  3. Elke Achtert, Ahmed Hettab, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2011). Spatial Outlier Detection: Data, Algorithms, Visualizations. SSTD, 512-516, Springer, 10.1007/978-3-642-22922-0_41, BibTeX
  4. Yong Shi, and Li Zhang (2011). COID: A cluster-outlier iterative detection approach to multi-dimensional data analysis. Knowl. Inf. Syst. 28(3), 709-733, 10.1007/s10115-010-0323-y, BibTeX
  5. Kai Ming Ting, Takashi Washio, Jonathan R. Wells, and Fei Tony Liu (2011). Density Estimation Based on Mass. ICDM, 715-724, IEEE, 10.1109/ICDM.2011.47, BibTeX
  6. Hans-Peter Kriegel, Peer Kröger, Erich Schubert, and Arthur Zimek (2011). Interpreting and Unifying Outlier Scores. SDM, 13-24, SIAM / Omnipress, 10.1137/1.9781611972818.2, BibTeX
  7. Claudia Plant (2011). SONAR: Signal De-mixing for Robust Correlation Clustering. SDM, 319-330, SIAM / Omnipress, 10.1137/1.9781611972818.28, BibTeX
  8. Anca Maria Ivanescu, Thivaharan Albin, Dirk Abel, and Thomas Seidl (2011). Employing correlation clustering for the identification of piecewise affine models. Proceedings of the 2011 workshop on Knowledge discovery, modeling and simulation - KDMS ‘11, ACM Press, 10.1145/2023568.2023575
  9. Stephan Günnemann, Hardy Kremer, and Thomas Seidl (2011). An extension of the PMML standard to subspace clustering models. Proceedings of the 2011 workshop on Predictive markup language modeling - PMML ‘11, ACM Press, 10.1145/2023598.2023605
  10. Resat Selbas, Arzu Sencan, and Ecir U. (2011). Data Mining Method For Energy System Aplications. Knowledge-Oriented Applications in Data Mining, InTech, 10.5772/13710
  11. Emmanuel Müller, Ira Assent, Stephan Günnemann, Patrick Gerwert, Matthias Hannen, Timm Jansen, and Thomas Seidl (2011). A Framework for Evaluation and Exploration of Clustering Algorithms in Subspaces of High Dimensional Databases. BTW, 347-366, GI, BibTeX
  12. Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2011). Evaluation of Multiple Clustering Solutions. MultiClust@ECML/PKDD, 55-66, CEUR-WS.org, BibTeX
  13. Johan Mazel (2011). Unsupervised network anomaly detection. (Détection non supervisée d’anomalies dans les réseaux de communication). INSA Toulouse, France, BibTeX
  14. Bilkis Jamal Ferdosi (2011). Scalable analysis and visualization of high-dimensional astronomical data sets. s.n. 9789036749633
  15. Iliya Mitov (2011). Class association rule mining using multidimensional numbered information spaces.
  16. Ευλάμπιος Αποστολίδης (2011). Συγκριτική μελέτη μεθόδων κατασκευής του R* TREE με όρους αποδοτικότητας για ερωτήματα κοντινότερου γείτονα σε πολυδιάστατους χώρους δεδομένων. Πανεπιστήμιο Μακεδονίας Οικονομικών και Κοινωνικών Επιστημών

2010

  1. Elke Achtert, Hans-Peter Kriegel, Lisa Reichert, Erich Schubert, Remigius Wojdanowski, and Arthur Zimek (2010). Visual Evaluation of Outlier Detection Models. DASFAA (2), 396-399, Springer, 10.1007/978-3-642-12098-5_34, BibTeX
  2. Dominik Benz, Andreas Hotho, Robert Jäschke, Beate Krause, Folke Mitzlaff, Christoph Schmitz, and Gerd Stumme (2010). The social bookmark and publication management system bibsonomy - A platform for evaluating and demonstrating Web 2.0 research. VLDB J. 19(6), 849-875, 10.1007/s00778-010-0208-4, BibTeX
  3. Arik Messerman, Tarik Mustafic, Seyit Ahmet Çamtepe, and Sahin Albayrak (2010). A generic framework and runtime environment for development and evaluation of behavioral biometrics solutions. ISDA, 136-141, IEEE, 10.1109/ISDA.2010.5687276, BibTeX
  4. Bilkis J. Ferdosi, Hugo Buddelmeijer, Scott C. Trager, Michael H. F. Wilkinson, and Jos B. T. M. Roerdink (2010). Finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological operators. IEEE VAST, 35-42, IEEE, 10.1109/VAST.2010.5652450, BibTeX
  5. Tobias Emrich, Hans-Peter Kriegel, Peer Kröger, Matthias Renz, and Andreas Züfle (2010). Boosting spatial pruning: on optimal pruning of MBRs. SIGMOD Conference, 39-50, ACM, 10.1145/1807167.1807174, BibTeX
  6. Kai Ming Ting, Guang-Tong Zhou, Fei Tony Liu, and James Swee Chuan Tan (2010). Mass estimation and its applications. KDD, 989-998, ACM, 10.1145/1835804.1835929, BibTeX
  7. Tobias Emrich, Franz Graf, Hans-Peter Kriegel, Matthias Schubert, and Marisa Thoma (2010). On the impact of flash SSDs on spatial indexing. DaMoN, 3-8, ACM, 10.1145/1869389.1869390, BibTeX
  8. Emmanuel Alexander Müller (2010). Efficient knowledge discovery in subspaces of high dimensional databases. 1-270, RWTH Aachen University, BibTeX
  9. Albert Hein, and Thomas Kirste (2010). Unsupervised detection of motion primitives in very high dimensional sensor data. BMI, 22-37, CEUR-WS.org

2009

  1. Hans-Peter Kriegel, Peer Kröger, Erich Schubert, and Arthur Zimek (2009). Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data. PAKDD, 831-838, Springer, 10.1007/978-3-642-01307-2_86, BibTeX
  2. Elke Achtert, Thomas Bernecker, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2009). ELKI in Time: ELKI 0.2 for the Performance Evaluation of Distance Measures for Time Series. SSTD, 436-440, Springer, 10.1007/978-3-642-02982-0_35, BibTeX
  3. Gabriela Moise, Arthur Zimek, Peer Kröger, Hans-Peter Kriegel, and Jörg Sander (2009). Subspace and projected clustering: experimental evaluation and analysis. Knowl. Inf. Syst. 21(3), 299-326, 10.1007/s10115-009-0226-y, BibTeX
  4. Hans-Peter Kriegel, Peer Kröger, and Arthur Zimek (2009). Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering. ACM Trans. Knowl. Discov. Data 3(1), 1:1-1:58, 10.1145/1497577.1497578, BibTeX
  5. Hans-Peter Kriegel, Peer Kröger, Erich Schubert, and Arthur Zimek (2009). LoOP: local outlier probabilities. CIKM, 1649-1652, ACM, 10.1145/1645953.1646195, BibTeX
  6. Arthur Zimek (2009). Correlation clustering. SIGKDD Explor. 11(1), 53-54, 10.1145/1656274.1656286, BibTeX

2008

  1. Elke Achtert, Hans-Peter Kriegel, and Arthur Zimek (2008). ELKI: A Software System for Evaluation of Subspace Clustering Algorithms. SSDBM, 580-585, Springer, 10.1007/978-3-540-69497-7_41, BibTeX
  2. Hans-Peter Kriegel, Peer Kröger, and Arthur Zimek (2008). Detecting clusters in moderate-to-high dimensional data: subspace clustering, pattern-based clustering, and correlation clustering. Proc. VLDB Endow. 1(2), 1528-1529, 10.14778/1454159.1454223, BibTeX

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