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,, 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.


  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/
  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


  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,, 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).


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  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


  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).


  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,, 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


  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,


  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


  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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