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 does contain errors. Where possible, we try to use metadata from DBLP, CrossRef.org, 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.

2017

  1. Abdulrahman H. Altalhi, José María Luna, M. A. Vallejo, and Sebastián Ventura (2017). Evaluation and comparison of open source software suites for data mining and knowledge discovery. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 3 7(3), Wiley Periodicals, Inc, 10.1002/widm.1204, BibTeX
  2. Adam Byron (2017). Clustering and Network Analysis of Reverse Phase Protein Array Data. Methods in Molecular Biology, 171-191, Springer New York, 10.1007/978-1-4939-6990-6_12
  3. Charu C. Aggarwal (2017). Applications of Outlier Analysis. Outlier Analysis, 399-422, Springer International Publishing, 10.1007/978-3-319-47578-3_13
  4. Charu C. Aggarwal, and Saket Sathe (2017). Variance Reduction in Outlier Ensembles. Outlier Ensembles, 75-161, Springer International Publishing, 10.1007/978-3-319-54765-7_3
  5. Jakub Sawicki, Maciej Smolka, Marcin Los, Robert Schaefer, and Piotr Faliszewski (2017). Two-Phase Strategy Managing Insensitivity in Global Optimization. 20th European Conference on the Applications of Evolutionary Computation, 266-281, Springer, Cham, 10.1007/978-3-319-55849-3_18, BibTeX
  6. Christian Beilschmidt, Thomas Fober, Michael Mattig, and Bernhard Seeger (2017). Quality Measures for Visual Point Clustering in Geospatial Mapping. 15th International Symposium on Web and Wireless Geographical Information Systems, 153-168, Springer, Cham, 10.1007/978-3-319-55998-8_10, BibTeX
  7. Ankita Roy, Soumya Ray, and Radha Tamal Goswami (2017). Approaches and Challenges of Big Data Analytics—Study of a Beginner. Proceedings of the First International Conference on Intelligent Computing and Communication, 237-245, Springer Singapore, 10.1007/978-981-10-2035-3_25
  8. Johannes Schneider, and Michail Vlachos (2017). Scalable density-based clustering with quality guarantees using random projections. Data Mining and Knowledge Discovery 31(4), 972-1005, Springer US, 10.1007/s10618-017-0498-x
  9. Klaus Arthur Schmid, Andreas Zufle, Tobias Emrich, Matthias Renz, and Reynold Cheng (2017). Uncertain Voronoi cell computation based on space decomposition. GeoInformatica, 1-31, Springer US, 10.1007/s10707-017-0293-2
  10. 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. Journal of Intelligent Information Systems 2 48, 287-308, Springer US, 10.1007/s10844-016-0411-x, BibTeX
  11. 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. Machine Learning 1 106, 55-91, Springer US, 10.1007/s10994-016-5586-4, BibTeX
  12. 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. Journal of Ambient Intelligence and Humanized Computing 3 8, 419-434, Springer Berlin Heidelberg, 10.1007/s12652-016-0400-5, BibTeX
  13. Emre Güngör, and Ahmet Özmen (2017). Distance and density based clustering algorithm using Gaussian kernel. Expert Systems with Applications 69, 10-20, Elsevier BV, 10.1016/j.eswa.2016.10.022, BibTeX
  14. Elyse Allender, and Tomasz F. Stepinski (2017). Automatic, exploratory mineralogical mapping of CRISM imagery using summary product signatures. Icarus, 151-161, Elsevier BV, 10.1016/j.icarus.2016.08.022
  15. Sirisup Laohakiat, Suphakant Phimoltares, and Chidchanok Lursinsap (2017). A clustering algorithm for stream data with LDA-based unsupervised localized dimension reduction. Information Sciences 381, 104-123, Elsevier BV, 10.1016/j.ins.2016.11.018, BibTeX
  16. Francesco Gullo, Giovanni Ponti, Andrea Tagarelli, and Sergio Greco (2017). An information-theoretic approach to hierarchical clustering of uncertain data. Information Sciences 402, 199-215, Elsevier BV, 10.1016/j.ins.2017.03.030, BibTeX
  17. Alvin Chiang, Esther David, Yuh-Jye Lee, Guy Leshem, and Yi-Ren Yeh (2017). A study on anomaly detection ensembles. Journal of Applied Logic 21, 1-13, Elsevier BV, 10.1016/j.jal.2016.12.002, BibTeX
  18. Dominik Sacha, Michael Sedlmair, Leishi Zhang, John A. 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, Elsevier BV, 10.1016/j.neucom.2017.01.105
  19. Hannes Bitto, Beatrice Mörstedt, Sylvia Faschina, and Rolf-Dieter Stieglitz (2017). ADHS bei Erwachsenen. Zeitschrift für Psychiatrie, Psychologie und Psychotherapie, 121-131, Hogrefe Publishing Group, 10.1024/1661-4747/a000311
  20. Wesin Alves, Daniel Martins, Ubiratan Bezerra, and Aldebaro Klautau (2017). A Hybrid Approach for Big Data Outlier Detection from Electric Power SCADA System. IEEE Latin America Transactions, 57-64, Institute of Electrical and Electronics Engineers (IEEE), 10.1109/TLA.2017.7827888
  21. Peter Bailis, Edward Gan, Samuel Madden, Deepak Narayanan, Kexin Rong, and Sahaana Suri (2017). MacroBase: Prioritizing Attention in Fast Data. Proceedings of the 2017 ACM International Conference on Management of Data, 541-556, ACM, 10.1145/3035918.3035928, BibTeX
  22. Hubert, Rocío B., Maguitman, Ana G., Chesñevar, Carlos I., and Malamud, Marcos A. (2017). CitymisVis: a Tool for the Visual Analysis and Exploration of Citizen Requests and Complaints. Proceedings of the 10th International Conference on Theory and Practice of Electronic Governance, 22-25, ACM, 10.1145/3047273.3047320
  23. 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, 1, Inderscience Publishers, 10.1504/IJRET.2017.080867
  24. Onur Doğan (2017). ÜCRETSİZ VERİ MADENCİLİĞİ ARAÇLARI VE TÜRKİYE’DE BİLİNİRLİKLERİ ÜZERİNE BİR ARAŞTIRMA. Ege Stratejik Araştırmalar Dergisi 8(1), 77-93, 10.18354/esam.15352
  25. Ravi, Aakash (2017). Machine learning-based identification of separating features in molecular fragments. 20.500.11956/2093
  26. Yoshiyuki Harada, Yoriyuki Yamagata, Osamu Mizuno, and Eun-Hye Choi (2017). Log-based Anomaly Detection of CPS Using a Statistical Method. CoRR abs/1701.03249, BibTeX
  27. 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, BibTeX
  28. 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. PVLDB 7 10, 769-780, BibTeX

2016

  1. Joy Mustafi (2016). Natural Language Processing and Machine Learning for Big Data. Techniques and Environments for Big Data Analysis, 53-74, Springer International Publishing, 10.1007/978-3-319-27520-8_4
  2. Johannes Blömer, and Kathrin Bujna (2016). Adaptive Seeding for Gaussian Mixture Models. 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 296-308, Springer International Publishing, 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. 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 253-264, Springer International Publishing, 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. Proceedings of 3rd International Conference on Advanced Computing, Networking and Informatics, 557-567, Springer India, 10.1007/978-81-322-2529-4_58
  5. B. B. Gupta, Aakanksha Tewari, Ankit Kumar Jain, and Dharma P. Agrawal (2016). Fighting against phishing attacks: state of the art and future challenges. Neural Computing and Applications, 1-26, Springer London, 10.1007/s00521-016-2275-y
  6. Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2016). The (black) art of runtime evaluation: Are we comparing algorithms or implementations?. Knowledge and Information Systems, 1-38, Springer London, 10.1007/s10115-016-1004-2
  7. Junming Shao, Xinzuo Wang, Qinli Yang, Claudia Plant, and Christian Böhm (2016). Synchronization-based scalable subspace clustering of high-dimensional data. Knowledge and Information Systems, 1-29, Springer London, 10.1007/s10115-016-1013-1
  8. Guilherme O. 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 Mining and Knowledge Discovery 4 30, 891-927, Springer US, 10.1007/s10618-015-0444-8, BibTeX
  9. Ahmed Aleroud, and Aryya Gangopadhyay (2016). Multimode co-clustering for analyzing terrorist networks. Information Systems Frontiers, 1-22, Springer US, 10.1007/s10796-016-9712-4
  10. Bo Jiang, Fei-yue Qiu, and Li-ping Wang (2016). Multi-view clustering via simultaneous weighting on views and features. Applied Soft Computing 47, 304-315, Elsevier BV, 10.1016/j.asoc.2016.06.010, BibTeX
  11. Manal T. Adham, and Peter J. Bentley (2016). Evaluating clustering methods within the Artificial Ecosystem Algorithm and their application to bike redistribution in London. Biosystems 146, 43-59, Elsevier BV, 10.1016/j.biosystems.2016.04.008, BibTeX
  12. 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. Computer Speech & Language 35, 234-261, Elsevier BV, 10.1016/j.csl.2014.10.001, BibTeX
  13. Bo Jiang, Fei-yue Qiu, Li-ping Wang, and Zhenjun Zhang (2016). Bi-level weighted multi-view clustering via hybrid particle swarm optimization. Information Processing & Management 3 52, 387-398, Elsevier BV, 10.1016/j.ipm.2015.11.003, BibTeX
  14. 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 2016(0), Oxford University Press, 10.1093/database/baw145, BibTeX
  15. 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
  16. 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
  17. Dominik Mautz, Christian Böhm, and Claudia Plant (2016). Subspace Clustering Ensembles through Tensor Decomposition. 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), 1225-1234, IEEE, 10.1109/ICDMW.2016.0177, BibTeX
  18. 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 Transactions on Knowledge and Data Engineering 2 28(2), 510-523, IEEE, 10.1109/TKDE.2015.2480400, BibTeX
  19. David Ciechanowicz, Dominik Pelzer, Benedikt Bartenschlager, and Alois Knoll (2016). A Modular Power System Planning and Power Flow Simulation Framework for Generating and Evaluating Power Network Models. IEEE Transactions on Power Systems, 1-1, Institute of Electrical and Electronics Engineers (IEEE), 10.1109/TPWRS.2016.2602479
  20. Fabrizio Angiulli, and Fabio Fassetti (2016). Toward Generalizing the Unification with Statistical Outliers: The Gradient Outlier Factor Measure. ACM Transactions on Knowledge Discovery from Data (TKDD) 3 10(3), 27:1-27:26, ACM, 10.1145/2829956, BibTeX
  21. Hossein Hamooni, Biplob Debnath, Jianwu Xu, Hui Zhang, Guofei Jiang, and Abdullah Mueen (2016). LogMine: Fast Pattern Recognition for Log Analytics. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, 1573-1582, ACM, 10.1145/2983323.2983358, BibTeX
  22. Apurva Narechania, Richard Baker, Rob DeSalle, Barun Mathema, Sergios-Orestis Kolokotronis, Barry Kreiswirth, and Paul J. Planet (2016). Clusterflock: a flocking algorithm for isolating congruent phylogenomic datasets. GigaScience 5(1), 44, BioMed Central, 10.1186/s13742-016-0152-3
  23. Amit Verma, Iqbaldeep Kaur, and Amandeep Kaur (2016). Algorithmic Approach to Data Mining and Classification Techniques. Indian Journal of Science and Technology 9(28), 10.17485/ijst/2016/v9i28/88874
  24. Ivano Verzola, Alessandro Donati, Jose Martinez, Matthias Schubert, and Laszlo Somodi (2016). Project Sibyl: A Novelty Detection System for Human Spaceflight Operations. 14th International Conference on Space Operations, American Institute of Aeronautics and Astronautics (AIAA), 10.2514/6.2016-2405
  25. Alejandro Rituerto, Henrik Andreasson, Ana C. Murillo, Achim J. Lilienthal, and José Jesús Guerrero (2016). Building an Enhanced Vocabulary of the Robot Environment with a Ceiling Pointing Camera. Sensors 4 16(4), 493, Multidisciplinary Digital Publishing Institute, 10.3390/s16040493, BibTeX
  26. Merima Kulin, Carolina Fortuna, Eli De Poorter, Dirk Deschrijver, and Ingrid Moerman (2016). Data-Driven Design of Intelligent Wireless Networks: An Overview and Tutorial. Sensors 6 16(6), 790, Multidisciplinary Digital Publishing Institute, 10.3390/s16060790, BibTeX
  27. Hutter, S., Grande, E., and Kriesi, H. (2016). Politicising Europe. Cambridge University Press, 9781107129412
  28. Gang Chen, Haiying Zhang, and Caiming Xiong (2016). Maximum Margin Dirichlet Process Mixtures for Clustering. AAAI, 1491-1497, BibTeX
  29. Jeffrey Hudack, and Jae C. Oh (2016). Multi-Agent Sensor Data Collection with Attrition Risk. ICAPS, 166-174, BibTeX
  30. Zhiruo Zhao, Chilukuri K. Mohan, and Kishan G. Mehrotra (2016). Adaptive Sampling and Learning for Unsupervised Outlier Detection. FLAIRS Conference, 460-466, BibTeX
  31. Xu Han, Chee Keong Kwoh, and Jung-jae Kim (2016). Clustering based active learning for biomedical Named Entity Recognition. IJCNN, 1253-1260, BibTeX
  32. Sebastian Bothe, and Tamás Horváth (2016). The Partial Weighted Set Cover Problem with Applications to Outlier Detection and Clustering. LWDA, 335-346, BibTeX
  33. Erich Schubert, Michael Weiler, and Hans-Peter Kriegel (2016). SPOTHOT: Scalable Detection of Geo-spatial Events in Large Textual Streams. SSDBM, 8:1-8:12, BibTeX
  34. Peter Bailis, Deepak Narayanan, and Samuel Madden (2016). MacroBase: Analytic Monitoring for the Internet of Things. CoRR abs/1603.00567, BibTeX
  35. Weiyu Huang, and Alejandro Ribeiro (2016). Hierarchical Clustering Given Confidence Intervals of Metric Distances. CoRR abs/1610.04274, BibTeX
  36. Seyed Morteza Mousavi, Aaron Harwood, Shanika Karunasekera, and Mojtaba Maghrebi (2016). Geometry of Interest (GOI): Spatio-Temporal Destination Extraction and Partitioning in GPS Trajectory Data. CoRR abs/1603.04110, BibTeX
  37. Yannis Papanikolaou, Ioannis Katakis, and Grigorios Tsoumakas (2016). Hierarchical Partitioning of the Output Space in Multi-label Data. CoRR abs/1612.06083, BibTeX
  38. Johannes Schneider, and Thomas Locher (2016). Obfuscation using Encryption. CoRR abs/1612.03345, BibTeX
  39. Lei Xu, Chunxiao Jiang, Yong Ren, and Hsiao-Hwa Chen (2016). Microblog Dimensionality Reduction - A Deep Learning Approach. IEEE Trans. Knowl. Data Eng. 7 28, 1779-1789, BibTeX
  40. Klaus Arthur Schmid (2016). Searching and mining in enriched geo-spatial data. BibTeX
  41. Michael Weiler (2016). Event detection in high throughput social media. Ludwig-Maximilians-Universität München, BibTeX
  42. Anthony McCaffrey, and University Of Massachusetts (2016). Feature Type Spectrum Technique.
  43. Balfagih, Ahmed (2016). Direct Selling Business Lead Prediction by Social Media Data Mining.
  44. Brlečić Layer, Hrvoje (2016). Klasifikacija energetskih subjekata u Republici Hrvatskoj korištenjem otkrivanja znanja iz baza podataka. University of Zagreb. Faculty of Economics and Business.
  45. Fatemeh Riahi, and Oliver Schulte (2016). Propositionalization for Unsupervised Outlier Detection in Multi-Relational Data. The Twenty-Ninth International Flairs Conference
  46. Gajewski, B., and Martyn, T. (2016). Spatial data clustering in independent mobile environment. Measurement Automation Monitoring Vol. 62, No. 5
  47. Josua Krause, Aritra Dasgupta, Jean-Daniel Fekete, and Enrico Bertini (2016). SeekAView: An Intelligent Dimensionality Reduction Strategy for Navigating High-Dimensional Data Spaces. LDAV 2016 - IEEE 6th Symposium on Large Data Analysis and Visualization
  48. 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
  49. Karanja, Stephen K (2016). Density-based Cluster Analysis Of Fire Hot Spots In Kenya’s Wildlife Protected Areas. University of Nairobi
  50. Kostjens, P.A.R. (2016). Anomaly Detection in Application Log Data.
  51. Lee, Pawel (2016). Structure in Star Forming Regions. University of Sheffield
  52. PUTELLI, LUCA (2016). Estrazione di regole di associazione da dati RDF.
  53. Pang, Guansong, Ting, Kai Ming, Albrecht, David, and Jin, Huidong (2016). ZERO++: Harnessing the Power of Zero Appearances to Detect Anomalies in Large-Scale Data Sets. Journal of Artificial Intelligence Research 57, 593-620
  54. Porras Bernárdez, Francisco Daniel (2016). Extraction of User’s Stays and Transitions from GPS Logs: A Comparison of Three Spatio-Temporal Clustering Approaches.
  55. Puura, Joonas (2016). Tarkvara loomine erinevate k-keskmiste algoritmide rakendamiseks (Software for Clustering Using k-means Algorithms).
  56. Rampão, Talita de Souza, 1994- (2016). Mineração de dados em bases jurídicas: um estudo de caso.
  57. Rusch, Thomas, Hornik, Kurt, and Mair, Patrick (2016). Assessing and quantifying clusteredness: The OPTICS Cordillera. WU Vienna University of Economics and Business
  58. Silva, Bruno Miguel Nunes da (2016). Exploratory Cluster Analysis from Ubiquitous Data Streams using Self-Organizing Maps.
  59. Trusina Jan (2016). Implementace evolučního shlukování. České vysoké učení technické v Praze. Vypočetní a informační centrum.
  60. V. Ilango (2016). Forecasting Methods Based on Outlier Detection And Influential Point Observation on Clustering Techniques Using Financial Time Series Data.

2015

  1. Greg Hamerly, and Jonathan Drake (2015). Accelerating Lloyd’s Algorithm for k-Means Clustering. Partitional Clustering Algorithms, 41-78, Springer International Publishing, 10.1007/978-3-319-09259-1_2
  2. Monika Kofler, Andreas Beham, Stefan Wagner, and Michael Affenzeller (2015). Robust Storage Assignment in Warehouses with Correlated Demand. Computational Intelligence and Efficiency in Engineering Systems, 415-428, Springer International Publishing, 10.1007/978-3-319-15720-7_29, BibTeX
  3. Erich Schubert, Arthur Zimek, and Hans-Peter Kriegel (2015). Fast and Scalable Outlier Detection with Approximate Nearest Neighbor Ensembles. 20th International Conference on Database Systems for Advanced Applications, 19-36, Springer International Publishing, 10.1007/978-3-319-18123-3_2, BibTeX
  4. Taylor Arnold, and Lauren Tilton (2015). Image Data. Humanities Data in R, 113-129, Springer International Publishing, 10.1007/978-3-319-20702-5_8
  5. Markus Mauder, Markus Reisinger, Tobias Emrich, Andreas Züfle, Matthias Renz, Goce Trajcevski, and Roberto Tamassia (2015). Minimal Spatio-Temporal Database Repairs. 14th International Symposium on Spatial and Temporal Databases, 255-273, Springer International Publishing, 10.1007/978-3-319-22363-6_14, BibTeX
  6. Lasanthi Heendaliya, Michael Wisely, Dan Lin, Sahra Sedigh Sarvestani, and Ali R. Hurson (2015). Influence-Aware Predictive Density Queries Under Road-Network Constraints. 14th International Symposium on Spatial and Temporal Databases, 80-97, Springer International Publishing, 10.1007/978-3-319-22363-6_5, BibTeX
  7. Tobias Emrich, Klaus Arthur Schmid, Andreas Züfle, Matthias Renz, and Reynold Cheng (2015). Uncertain Voronoi Cell Computation Based on Space Decomposition. 14th International Symposium on Spatial and Temporal Databases, 98-116, Springer International Publishing, 10.1007/978-3-319-22363-6_6, BibTeX
  8. Bo Zhu, Alexandru Mara, and Alberto Mozo (2015). CLUS: Parallel Subspace Clustering Algorithm on Spark. East European Conference on Advances in Databases and Information Systems, 175-185, Springer International Publishing, 10.1007/978-3-319-23201-0_20, BibTeX
  9. Pengjie Ren, Peng Liu, Zhumin Chen, Jun Ma, and Xiaomeng Song (2015). Learning Similarity Functions for Urban Events Detection by Mining Hotline Phone Records. 17th Asia-Pacific Web Conference, 411-423, Springer International Publishing, 10.1007/978-3-319-25255-1_34, BibTeX
  10. Nadezhda Fedorova, Josep Blat, and David F. Nettleton (2015). Can Embedding Solve Scalability Issues for Mixed-Data Graph Clustering?. 21st European Conference on Parallel Processing, 481-492, Springer International Publishing, 10.1007/978-3-319-27308-2_39, BibTeX
  11. Tobias Emrich, Hans-Peter Kriegel, Peer Kröger, Johannes Niedermayer, Matthias Renz, and Andreas Züfle (2015). On reverse-k-nearest-neighbor joins. GeoInformatica 2 19(2), 299-330, Springer US, 10.1007/s10707-014-0215-5, BibTeX
  12. Arthur Zimek, and Jilles Vreeken (2015). The blind men and the elephant: on meeting the problem of multiple truths in data from clustering and pattern mining perspectives. Machine Learning 1-2 98(1-2), 121-155, Springer US, 10.1007/s10994-013-5334-y, BibTeX
  13. Heiko Paulheim, and Robert Meusel (2015). A decomposition of the outlier detection problem into a set of supervised learning problems. Machine Learning 2-3 100, 509-531, Springer US, 10.1007/s10994-015-5507-y, BibTeX
  14. Daniel Avila, and Iren Valova (2015). RADDACL2: a recursive approach to discovering density clusters. Progress in Artificial Intelligence 1-2 4(1-2), 21-36, Springer Berlin Heidelberg, 10.1007/s13748-015-0066-9, BibTeX
  15. Tamer F. Ghanem, Wail S. El-Kilani, Hatem M. Abdelkader, and Mohiy M. Hadhoud (2015). Fast Dimension-based Partitioning and Merging clustering algorithm. Applied Soft Computing 36, 143-151, Elsevier BV, 10.1016/j.asoc.2015.05.049, BibTeX
  16. Antonio Lavecchia (2015). Machine-learning approaches in drug discovery: methods and applications. Drug Discovery Today, 318-331, Elsevier BV, 10.1016/j.drudis.2014.10.012
  17. Francisco Maciá Pérez, José Vicente Berná-Martínez, Alberto Fernández Oliva, and Miguel Alfonso Abreu Ortega (2015). Algorithm for the detection of outliers based on the theory of rough sets. Decision Support Systems 75, 63-75, Elsevier BV, 10.1016/j.dss.2015.05.002, BibTeX
  18. Mohamed Bouguessa (2015). A practical outlier detection approach for mixed-attribute data. Expert Systems with Applications 22 42, 8637-8649, Elsevier BV, 10.1016/j.eswa.2015.07.018, BibTeX
  19. Wen-qian Liu, Jun Liu, Meng Wang, Qinghua Zheng, Wei Zhang, Lingyun Song, and Siyu Yao (2015). Faceted fusion of RDF data. Information Fusion 23, 16-24, Elsevier BV, 10.1016/j.inffus.2014.06.005, BibTeX
  20. Seok-Ho Yoon, Ki-Nam Kim, Jiwon Hong, Sang-Wook Kim, and Sunju Park (2015). A community-based sampling method using DPL for online social networks. Information Sciences 306, 53-69, Elsevier BV, 10.1016/j.ins.2015.02.014, BibTeX
  21. Bifan Wei, Jun Liu, Qinghua Zheng, Wei Zhang, Chenchen Wang, and Bei Wu (2015). DF-Miner: Domain-specific facet mining by leveraging the hyperlink structure of Wikipedia. Knowledge-Based Systems 77, 80-91, Elsevier BV, 10.1016/j.knosys.2015.01.001, BibTeX
  22. M. Peyro, M. Soheilypour, B.L. Lee, and M.R.K. Mofrad (2015). Evolutionarily Conserved Sequence Features Regulate the Formation of the FG Network at the Center of the Nuclear Pore Complex. Scientific Reports 5, 10.1038/srep15795
  23. Yang Zhao, Abhishek K. Shrivastava, and Kwok Leung Tsui (2015). Imbalanced Classification by Learning Hidden Data Structure. IIE Transactions, 0-0, Informa UK Limited, 10.1080/0740817X.2015.1110269
  24. Anand Mehta, and Onkar Dikshit (2015). Comparative study on projected clustering methods for hyperspectral imagery classification. Geocarto International, 1-12, Informa UK Limited, 10.1080/10106049.2015.1047416
  25. Panagiotis Barlas, Ivor Lanning, and Cathal Heavey (2015). A survey of open source data science tools. International Journal of Intelligent Computing and Cybernetics 3 8, 232-261, Emerald, 10.1108/IJICC-07-2014-0031, BibTeX
  26. Lei Xu, Chunxiao Jiang, and Yong Ren (2015). Deep learning in exploring semantic relatedness for microblog dimensionality reduction. 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 98-102, IEEE, 10.1109/GlobalSIP.2015.7418164, BibTeX
  27. Michael Wisely, Ali R. Hurson, and Sahra Sedigh Sarvestani (2015). An extensible simulation framework for evaluating centralized traffic prediction algorithms. 2015 International Conference on Connected Vehicles and Expo (ICCVE), 391-396, IEEE, 10.1109/ICCVE.2015.86, BibTeX
  28. Juan M. Banda, and Rafal A. Angryk (2015). Unsupervised Learning Techniques for Detection of Regions of Interest in Solar Images. 2015 IEEE International Conference on Data Mining Workshop (ICDMW), 582-588, IEEE, 10.1109/ICDMW.2015.61, BibTeX
  29. Guansong Pang, Kai Ming Ting, and David Albrecht (2015). LeSiNN: Detecting Anomalies by Identifying Least Similar Nearest Neighbours. 2015 IEEE International Conference on Data Mining Workshop (ICDMW), 623-630, IEEE, 10.1109/ICDMW.2015.62, BibTeX
  30. Erich Schubert, Michael Weiler, and Arthur Zimek (2015). Outlier Detection and Trend Detection: Two Sides of the Same Coin. 2015 IEEE International Conference on Data Mining Workshop (ICDMW), 40-46, IEEE, 10.1109/ICDMW.2015.79, BibTeX
  31. Fatemeh Riahi, and Oliver Schulte (2015). Model-Based Outlier Detection for Object-Relational Data. Computational Intelligence, 2015 IEEE Symposium Series on, 1590-1598, IEEE, 10.1109/SSCI.2015.224, BibTeX
  32. Milos Radovanovic, Alexandros Nanopoulos, and Mirjana Ivanovic (2015). Reverse Nearest Neighbors in Unsupervised Distance-Based Outlier Detection. Knowledge and Data Engineering, IEEE Transactions on 5 27(5), 1369-1382, IEEE, 10.1109/TKDE.2014.2365790, BibTeX
  33. Hezheng Yin, Joseph Bahman Moghadam, and Armando Fox (2015). Clustering Student Programming Assignments to Multiply Instructor Leverage. Proceedings of the Second (2015) ACM Conference on Learning @ Scale, 367-372, ACM, 10.1145/2724660.2728695, BibTeX
  34. Neil Scicluna, and Christos-Savvas Bouganis (2015). ARC 2014: A Multidimensional FPGA-Based Parallel DBSCAN Architecture. ACM Transactions on Reconfigurable Technology and Systems (TRETS) 1 9(1), 2:1-2:15, ACM, 10.1145/2724722, BibTeX
  35. Ricardo J. G. B. Campello, Davoud Moulavi, Arthur Zimek, and Jörg Sander (2015). Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection. ACM Transactions on Knowledge Discovery from Data (TKDD) 1 10(1), 5:1-5:51, ACM, 10.1145/2733381, BibTeX
  36. Yikai Gong, Fengmin Deng, and Richard O. Sinnott (2015). Identification of (near) Real-time Traffic Congestion in the Cities of Australia through Twitter. Proceedings of the ACM First International Workshop on Understanding the City with Urban Informatics, 7-12, ACM, 10.1145/2811271.2811276, BibTeX
  37. Charu C. Aggarwal, and Saket Sathe (2015). Theoretical Foundations and Algorithms for Outlier Ensembles. ACM SIGKDD Explorations Newsletter 1 17(1), 24-47, ACM, 10.1145/2830544.2830549, BibTeX
  38. Hugo Zeberg, Hugh P. C. Robinson, and Peter Århem (2015). Density of voltage-gated potassium channels is a bifurcation parameter in pyramidal neurons. Journal of Neurophysiology 113(2), 537-549, American Physiological Society, 10.1152/jn.00907.2013
  39. Patrick Oesterling, Patrick Jähnichen, Gerhard Heyer, and Gerik Scheuermann (2015). Topological visual analysis of clusterings in high-dimensional information spaces. it - Information Technology 1 57, 3-10, Walter de Gruyter GmbH, 10.1515/itit-2014-1073, BibTeX
  40. I. A. Pestunov, S. A. Rylov, and V. B. Berikov (2015). Hierarchical clustering algorithms for segmentation of multispectral images. Optoelectronics, Instrumentation and Data Processing 51(4), 329-338, Allerton Press, 10.3103/S8756699015040020
  41. Mansi Gera, and Shivani Goel (2015). Data Mining - Techniques, Methods and Algorithms: A Review on Tools and their Validity. International Journal of Computer Applications, 22-29, Foundation of Computer Science, 10.5120/19926-2042
  42. Smita Chormunge, and Sudarson Jena (2015). Efficiency and Effectiveness of Clustering Algorithms for High Dimensional Data. International Journal of Computer Applications, 35-40, Foundation of Computer Science, 10.5120/ijca2015906144
  43. Rajendiran, Swetha (2015). Learning classification algorithms in data mining. 10211.3/139358
  44. Collazo Santiago, Bryan Omar (2015). Machine learning blocks. Massachusetts Institute of Technology, 1721.1/100301
  45. Oxenham, M., and Buckley, H. (2015). The Routledge Handbook of Bioarchaeology in Southeast Asia and the Pacific Islands. Taylor & Francis, 9781317534013
  46. Barcelo, J.A., and Bogdanovic, I. (2015). Mathematics and Archaeology. CRC Press, 9781482226829
  47. Renz, M., Shahabi, C., Zhou, X., and Cheema, M.A. (2015). Database Systems for Advanced Applications: 20th International Conference, DASFAA 2015, Hanoi, Vietnam, April 20-23, 2015, Proceedings. Springer International Publishing, 9783319181233
  48. Claramunt, C., Schneider, M., Wong, R.C.W., Xiong, L., Loh, W.K., Shahabi, C., and Li, K.J. (2015). Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. Proceedings. Springer International Publishing, 9783319223636
  49. Voronkov, A., and Virbitskaite, I. (2015). Perspectives of System Informatics: 9th International Ershov Informatics Conference, PSI 2014, St. Petersburg, Russia, June 24-27, 2014. Revised Selected Papers. Springer Berlin Heidelberg, 9783662468234
  50. Veit Köppen, Mario Hildebrandt, and Martin Schäler (2015). On performance optimization potentials regarding data classification in forensics. BTW Workshops, 21-36, BibTeX
  51. Jürgen Hermes, Michael Richter, and Claes Neuefeind (2015). Automatic Induction of German Aspectual Verb Classes in a Distributional Framework. GSCL, 122-129, BibTeX
  52. Alvin Chiang, and Yi-Ren Yeh (2015). Anomaly Detection Ensembles: In Defense of the Average. WI-IAT (3), 207-210, BibTeX
  53. David Alfter (2015). Language Segmentation. CoRR abs/1510.01717, BibTeX
  54. Ling Chen, Ting Yu, and Rada Chirkova (2015). WaveCluster with Differential Privacy. CoRR abs/1508.00192, BibTeX
  55. Mehrdad Ghadiri, Amin Aghaee, and Mahdieh Soleymani Baghshah (2015). Active Distance-Based Clustering using K-medoids. CoRR abs/1512.03953, BibTeX
  56. Keqian Li (2015). On Integrating Information Visualization Techniques into Data Mining: A Review. CoRR abs/1503.00202, BibTeX
  57. Fabien André, Anne-Marie Kermarrec, and Nicolas Le Scouarnec (2015). Cache locality is not enough: High-Performance Nearest Neighbor Search with Product Quantization Fast Scan. PVLDB 4 9, 288-299, BibTeX
  58. Erich Schubert, Alexander Koos, Tobias Emrich, Andreas Züfle, Klaus Arthur Schmid, and Arthur Zimek (2015). A Framework for Clustering Uncertain Data. PVLDB 12 8, 1976-1979, BibTeX
  59. Johannes Niedermayer (2015). Complex queries and complex data: challenges in similarity search. Ludwig-Maximilians-Universität München, BibTeX
  60. Matthias Rohr (2015). Workload-sensitive Timing Behavior Analysis for Fault Localization in Software Systems. Universitätsbibliothek Kiel, BibTeX
  61. 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). UBO, BibTeX
  62. Armon, Gilad, Loinger, Adiel, Blatt, Uri, and Siegman, Shahar (2015). BENCHMARKING IN ONLINE ADVERTISING.
  63. Bhinge, Akshay Vishwanath (2015). A comparative study on data mining tools.
  64. Campos, Guilherme Oliveira (2015). Estudo, avaliação e comparação de técnicas de detecção não supervisionada de outliers. Biblioteca Digital de Teses e Dissertações da Universidade de São Paulo
  65. Fernández Sánchez, Irene (2015). Diseño de una metodología de evaluación de servicios públicos basada en modelos analíticos sobre datos abiertos y de redes sociales.
  66. Heendaliya, Lasanthi Nilmini (2015). Enabling near-term prediction of status for intelligent transportation systems: Management techniques for data on mobile objects. Missouri University of Science and Technology
  67. Jonathan von Brünken, Michael E. Houle, and Arthur Zimek (2015). Intrinsic Dimensional Outlier Detection in High-Dimensional Data.
  68. 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
  69. Křeček Martin (2015). Rozšíření platformy Clueminer o grafové algoritmy. České vysoké učení technické v Praze. Vypočetní a informační centrum.
  70. 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
  71. 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
  72. Levin, Carl, and Hakansson, Christopher (2015). Clustering driver’s destinations - using internal evaluation to adaptively set parameters.
  73. Liao, Yan, Hua, Jialin, and Zhu, Wensheng (2015). An Effective Divide-and-Merge Method for Hierarchical Clustering.
  74. Mamani Rodríguez, Zoraida Emperatriz, and Mamani Rodríguez, Zoraida Emperatriz (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
  75. Micenková, Barbora (2015). Outlier Detection and Explanation for Domain Experts. Department of Computer Science, University of Aarhus
  76. Ondego, Gordon, O (2015). A comparative study of decision Tree and Naïve Bayesian Classifiers on Verbal Autopsy Datasets. University of Nairobi
  77. Pang, Guansong (2015). Anomaly detection based on zero appearances in subspaces. Monash University. Faculty of Information Technology. Clayton School of Information Technology
  78. Silén, Markku (2015). Symbolisen ja numeerisen laskennan ohjelmat opiskelijan apuna. Lapin ammattikorkeakoulu
  79. Van Craenendonck, Toon, and Blockeel, Hendrik (2015). Limitations of using constraint set utility in semi-supervised clustering.
  80. 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(2 (110)), Закрытое акционерное общество Научно-исследовательский институт “Центрпрограммсистем”
  81. 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 Interdisciplinary Reviews: Data Mining and Knowledge Discovery 3 4(3), 161-177, Wiley Periodicals, Inc, 10.1002/widm.1127, BibTeX
  2. Mathilde Sahuguet, and Benoit Huet (2014). Mining the Web for Multimedia-Based Enriching. MultiMedia Modeling, 263-274, Springer International Publishing, 10.1007/978-3-319-04117-9_24, BibTeX
  3. Neil Scicluna, and Christos-Savvas Bouganis (2014). FPGA-Based Parallel DBSCAN Architecture. 10th International Symposium on Applied Reconfigurable Computing, 1-12, Springer International Publishing, 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. 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 461-473, Springer International Publishing, 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. 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 510-521, Springer International Publishing, 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. European Semantic Web Conference, 477-482, Springer International Publishing, 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. 7th International Conference on Similarity Search and Applications, 151-163, Springer International Publishing, 10.1007/978-3-319-11988-5_14, BibTeX
  8. Kirill Smirnov, George Chernishev, Pavel Fedotovsky, George Erokhin, and Kirill Cherednik (2014). The Study of Multidimensional R-Tree-Based Index Scalability in Multicore Environment. 9th International Andrei Ershov Memorial Conference on Perspectives of System Informatics, 266-272, Springer Berlin Heidelberg, 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. International Journal on Digital Libraries 3-4 14(3-4), 167-179, Springer Berlin Heidelberg, 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 Mining and Knowledge Discovery 1 28(1), 190-237, Springer US, 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. Journal of Intelligent Information Systems 2 42(2), 307-332, Springer US, 10.1007/s10844-013-0299-7, BibTeX
  12. Chen Lin, Runquan Xie, Xinjun Guan, Lei Li, and Tao Li (2014). Personalized news recommendation via implicit social experts. Information Sciences 254, 1-18, Elsevier BV, 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 Recognition 8 47, 2702-2720, Elsevier BV, 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. Journal of Infrastructure Systems, 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. Behavior, Economic and Social Computing (BESC), 2014 International Conference on, 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. Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on, 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. Data Engineering (ICDE), 2014 IEEE 30th International Conference on, 88-99, IEEE, 10.1109/ICDE.2014.6816642, BibTeX
  18. Tharindu R. Bandaragoda, Kai Ming Ting, David Albrecht, Fei Tony Liu, and Jonathan R. Wells (2014). Efficient Anomaly Detection by Isolation Using Nearest Neighbour Ensemble. Data Mining Workshop (ICDMW), 2014 IEEE International Conference on, 698-705, IEEE, 10.1109/ICDMW.2014.70, BibTeX
  19. Ghanem, Tamer F., Elkilani, Wail S., Ahmed, Hatem S., and Hadhoud, Mohiy M. (2014). DPM: Fast and scalable clustering algorithm for large scale high dimensional datasets. Computer Engineering Conference (ICENCO), 2014 10th International, 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. Pattern Recognition (ICPR), 2014 22nd International Conference on, 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. Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2014 37th International Convention on, 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. Research Challenges in Information Science (RCIS), 2014 IEEE Eighth International Conference on, 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. Proceedings of the 2014 SIAM International Conference on Data Mining, 542-550, Society for Industrial & Applied Mathematics (SIAM), 10.1137/1.9781611973440.63, BibTeX
  24. Mohamed Bouguessa (2014). A Mixture Model-Based Combination Approach for Outlier Detection. International Journal on Artificial Intelligence Tools 4 23, 1460021, World Scientific Pub Co Pte Lt, 10.1142/S0218213014600215, BibTeX
  25. Arthur Zimek, Ricardo J. G. B. Campello, and Jörg Sander (2014). Data perturbation for outlier detection ensembles. Proceedings of the 26th International Conference on Scientific and Statistical Database Management, 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. Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, 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. Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, 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. Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, 871-880, ACM, 10.1145/2623330.2623740, BibTeX
  29. 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, 10.1371/journal.pone.0090109
  30. 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. IJCBDD 2/3 7, 113-129, Inderscience Publishers, 10.1504/IJCBDD.2014.061655, BibTeX
  31. 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. Mobile Computing, Applications and Services (MobiCASE), 2014 6th International Conference on, 10-19, IEEE, 10.4108/icst.mobicase.2014.257683, BibTeX
  32. 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, 10.5441/002/edbt.2014.31, BibTeX
  33. Ma,R.J., and Yu,N.Y. (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), 1969.1/152321
  34. Mollá Santiago, Sheila (2014). Generalització de mètodes de density-based clustering a dades mixtes. Universitat Politècnica de Catalunya, 2099.1/21766
  35. Mehta, A., and Dikshit, O. (2014). SPCA Assisted Correlation Clustering of Hyperspectral Imagery. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-8, 111-116, Copernicus GmbH, doi:10.5194/isprsannals-II-8-111-2014
  36. Aljarah, Ibrahim Mithgal (2014). MapReduce-enabled scalable nature-inspired approaches for clustering. NORTH DAKOTA STATE UNIVERSITY, 978-1-303-83676-3
  37. Valentine, S. (2014). Sentiment Analysis 19 Success Secrets - 19 Most Asked Questions On Sentiment Analysis - What You Need To Know. Emereo Publishing, 9781488535208
  38. 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, BibTeX
  39. 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, BibTeX
  40. Stephan Günnemann, Hardy Kremer, Matthias Hannen, and Thomas Seidl (2014). KDD-SC: Subspace Clustering Extensions for Knowledge Discovery Frameworks. CoRR abs/1407.3850, BibTeX
  41. MingJie Tang, Ruby Y. Tahboub, Walid G. Aref, Mikhail J. Atallah, Qutaibah M. Malluhi, Mourad Ouzzani, and Yasin N. Silva (2014). Similarity Group-by Operators for Multi-dimensional Relational Data. CoRR abs/1412.4842, BibTeX
  42. Albrecht Zimmermann (2014). A feature construction framework based on outlier detection and discriminative pattern mining. CoRR abs/1407.4668, BibTeX
  43. Xiao He (2014). Multi-purpose exploratory mining of complex data. Ludwig-Maximilians-Universität München, BibTeX
  44. Richard Röttger (2014). Active transitivity clustering of large-scale biomedical datasets. BibTeX
  45. Michael Davis (2014). Discovering patterns and anomalies in graphs with discrete and numeric attributes. Queen’s University Belfast, BibTeX
  46. AR Sin (2014). Modeling the environment with egocentric vision systems. TESIS-2015-012, Universidad de Zaragoza, Prensas de la Universidad
  47. Bagnacani, Andrea (2014). Linked Data e bibliometriche: un indice di multidisciplinarieta nel Semantic Publishing.
  48. Dominique Legallois, Solen Quiniou, Peggy Cellier, and Thierry Charnois (2014). Graph Mining under Linguistic Constraints for Exploring Large Texts. Instituto Politécnico Nacional
  49. Erbacher, Robert F, and Pino, Robinson (2014). Open Source Software Tools for Anomaly Detection Analysis. ARL-MR-0869, ARMY RESEARCH LAB ADELPHI MD COMPUTATIONAL AND INFORMATION SCIENCES DIRECTORATE
  50. Gross, João Luiz Grave (2014). URSA: um framework para agrupamento de dados e validação de resultados (URSA: a framework for data clustering and data analysis).
  51. Indaco, Francesco (2014). HIERARCHICAL CLUSTERING USING LEVEL SETS. San Jose State University
  52. Kelemen, Reka Katalin (2014). Mathematical modeling of T cell clustering following malaria infection in mice. University of Tennessee, Knoxville
  53. Larsson, Henrik, and Lindqvist, Erik (2014). Unsupervised Outlier Detection in Software Engineering. Chalmers University of Technology
  54. LÖFROTH, BJÖRN (2014). Mobile traffic dataset comparisons throughcluster analysis of radio network event sequences.
  55. PADOVANO, NICOLA, and POLO, ELIA FILIBERTO (2014). Progetto e realizzazione di un framework per Neosperience sul clustering di reti sociali.
  56. 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.
  57. Sohail, Muhammad (2014). Calculation of Energy Footprint of Manufacturing Assets.
  58. Zhang, Haofan (2014). Spectral Ranking and Unsupervised Feature Selection for Point, Collective and Contextual Anomaly Detection.
  59. Zwietasch, Tim (2014). Detecting anomalies in system log files using machine learning techniques. Uni Stuttgart - Universitätsbibliothek
  60. van Oirschot, Y.P.J.M. (2014). Using trace clustering for configurable process discovery explained by eent log data.

2013

  1. Zeyar Aung (2013). Database Systems for the Smart Grid. Smart Grids, 151-168, Springer London, 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). An Introduction to Outlier Analysis. Outlier Analysis, 1-40, Springer New York, 10.1007/978-1-4614-6396-2_1
  4. Charu C. Aggarwal (2013). Applications of Outlier Analysis. Outlier Analysis, 373-400, Springer New York, 10.1007/978-1-4614-6396-2_12
  5. Charu C. Aggarwal (2013). High-Dimensional Outlier Detection: The Subspace Method. Outlier Analysis, 135-167, Springer New York, 10.1007/978-1-4614-6396-2_5
  6. Jordi Nin, David Carrera, and Daniel Villatoro (2013). On the Use of Social Trajectory-Based Clustering Methods for Public Transport Optimization. Citizen in Sensor Networks, 59-70, Springer International Publishing, 10.1007/978-3-319-04178-0_6, BibTeX
  7. 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 Berlin Heidelberg, 10.1007/978-3-642-28696-4_8
  8. Mariusz Oszust, and Marian Wysocki (2013). Clustering and Classification of Time Series Representing Sign Language Words. Artificial Intelligence and Soft Computing, 218-229, Springer Berlin Heidelberg, 10.1007/978-3-642-38610-7_21, BibTeX
  9. Rana Momtaz, Nesma Mohssen, and Mohammad A. Gowayyed (2013). DWOF: A Robust Density-Based Outlier Detection Approach. 6th Iberian Conference on Pattern Recognition and Image Analysis, 517-525, Springer Berlin Heidelberg, 10.1007/978-3-642-38628-2_61, BibTeX
  10. Felix Stahlberg, Tim Schlippe, Stephan Vogel, and Tanja Schultz (2013). Pronunciation Extraction from Phoneme Sequences through Cross-Lingual Word-to-Phoneme Alignment. Statistical Language and Speech Processing, 260-272, Springer Berlin Heidelberg, 10.1007/978-3-642-39593-2_23, BibTeX
  11. Tobias Emrich, Hans-Peter Kriegel, Peer Kröger, Johannes Niedermayer, Matthias Renz, and Andreas Züfle (2013). Reverse-k-Nearest-Neighbor Join Processing. Advances in Spatial and Temporal Databases, 277-294, Springer Berlin Heidelberg, 10.1007/978-3-642-40235-7_16, BibTeX
  12. Erich Schubert, Arthur Zimek, and Hans-Peter Kriegel (2013). Geodetic Distance Queries on R-Trees for Indexing Geographic Data. Advances in Spatial and Temporal Databases, 146-164, Springer Berlin Heidelberg, 10.1007/978-3-642-40235-7_9, BibTeX
  13. 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?. 3rd International Conference on Theory and Practice of Digital Libraries, 96-107, Springer Berlin Heidelberg, 10.1007/978-3-642-40501-3_10, BibTeX
  14. 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 Berlin Heidelberg, 10.1007/978-3-642-40897-7_17, BibTeX
  15. Xuan Hong Dang, Barbora Micenková, Ira Assent, and Raymond T. Ng (2013). Local Outlier Detection with Interpretation. Machine Learning and Knowledge Discovery in Databases, 304-320, Springer Berlin Heidelberg, 10.1007/978-3-642-40994-3_20, BibTeX
  16. Part Pramokchon, and Punpiti Piamsa-nga (2013). An Unsupervised, Fast Correlation-Based Filter for Feature Selection for Data Clustering. Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013), 87-94, Springer Singapore, 10.1007/978-981-4585-18-7_10, BibTeX
  17. 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 Berlin Heidelberg, 10.1007/s00894-013-1916-7
  18. Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Fei Tony Liu, and Sunil Aryal (2013). DEMass: a new density estimator for big data. Knowledge and Information Systems 3 35(3), 493-524, Springer-Verlag, 10.1007/s10115-013-0612-3, BibTeX
  19. Kai Ming Ting, Guang-Tong Zhou, Fei Tony Liu, and Swee Chuan Tan (2013). Mass estimation. Machine Learning 1 90(1), 127-160, Springer US, 10.1007/s10994-012-5303-x, BibTeX
  20. Ibrahim Aljarah, and Simone A. Ludwig (2013). A new clustering approach based on Glowworm Swarm Optimization. Evolutionary Computation (CEC), 2013 IEEE Congress on, 2642-2649, IEEE, 10.1109/CEC.2013.6557888, BibTeX
  21. Yang Zhao, and Abhishek K. Shrivastava (2013). Combating Sub-Clusters Effect in Imbalanced Classification. Data Mining (ICDM), 2013 IEEE 13th International Conference on, 1295-1300, IEEE, 10.1109/ICDM.2013.105, BibTeX
  22. Barbora Micenková, Raymond T. Ng, Xuan Hong Dang, and Ira Assent (2013). Explaining Outliers by Subspace Separability. Data Mining (ICDM), 2013 IEEE 13th International Conference on, 518-527, IEEE, 10.1109/ICDM.2013.132, 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. Computer Communications Workshops (INFOCOM WKSHPS), 2013 IEEE Conference on, 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. 2013 17th International Conference on Information Visualisation, 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. Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, 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. Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, 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. Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, 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. Proceedings of the 22nd ACM international conference on Conference on information & knowledge management, 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. Proceedings of the 7th ACM conference on Recommender systems, 209-212, ACM, 10.1145/2507157.2507198, BibTeX
  30. 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, 10.1371/journal.pone.0073831
  31. Martin Behnisch, Gotthard Meinel, Sebastian Tramsen, and Markus Diesselmann (2013). Using quadtree representations in building stock visualization and analysis. Erdkunde, 151-166, Erdkunde, 10.3112/erdkunde.2013.02.04
  32. PrakashVerma, Jai, Patel, Bankim, and Patel, Atul (2013). Web Mining: Opinion and Feedback Analysis for Educational Institutions. International Journal of Computer Applications 84(6), 17-22, 10.5120/14579-2800
  33. Davenport, T.H., and Kim, J. (2013). Keeping Up with the Quants: Your Guide to Understanding and Using Analytics. Harvard Business Review Press, 9781422187265
  34. Menken, I. (2013). Data Mining Guidance - Real World Application, Templates, Documents, and Examples of the use of Data Mining in the Public Domain. Emereo Publishing, 9781486460458
  35. Arthur Zimek (2013). Clustering High-Dimensional Data. Data Clustering: Algorithms and Applications, 201-230, BibTeX
  36. Tobias Emrich, Peer Kröger, Johannes Niedermayer, Matthias Renz, and Andreas Züfle (2013). A Mutual Pruning Approach for RkNN Join Processing. BTW, 21-35, BibTeX
  37. Johannes Blömer, and Kathrin Bujna (2013). Simple Methods for Initializing the EM Algorithm for Gaussian Mixture Models. CoRR abs/1312.5946, BibTeX
  38. Martin Schäler, Alexander Grebhahn, Reimar Schröter, Sandro Schulze, Veit Köppen, and Gunter Saake (2013). QuEval: Beyond high-dimensional indexing a la carte. PVLDB 14 6, 1654-1665, BibTeX
  39. Tobias Emrich (2013). Coping with distance and location dependencies in spatial, temporal and uncertain data. Ludwig-Maximilians-Universität München, BibTeX
  40. Daniel Kuntze (2013). Practical algorithms for clustering and modeling large data sets: analysis and improvements. 1-130, Paderborn, Universität Paderborn, Diss., 2013, BibTeX
  41. Erich Schubert (2013). Generalized and efficient outlier detection for spatial, temporal, and high-dimensional data mining. 1-262, Ludwig-Maximilians-Universität München, BibTeX
  42. Andreas Züfle (2013). Similarity search and mining in uncertain spatial and spatio-temporal databases. 1-397, Ludwig-Maximilians-Universität München, BibTeX
  43. Matthew Orlinski (2013). Neighbour discovery and distributed spatio-temporal cluster detection in pocket switched networks. University of Manchester, BibTeX
  44. Claire Elizabeth Q (2013). Machine learning analysis of the cultural and cross-cultural aspects of beauty in music. Aberystwyth University, BibTeX
  45. Alves, Stefan Eduard Raposo (2013). Towards improving WEBSOM with multi-word expressions. Faculdade de Ciências e Tecnologia
  46. Barandun, Curdin, Derungs, Stefan, and Paulaitis, Gino (2013). Mixtape: Analyse und Erstellung Ähnlichkeitsanalyse von Musik anhand einer praktischen Implementation.
  47. Daigle, Bruno (2013). Méthodes bioinformatiques pour l’évaluation de la classification du virus du papillome humain.
  48. Fares, Elie (2013). Real-time systems refinement: application to the verification of web services.
  49. Gupta, Manish (2013). Outlier detection for information networks. University of Illinois at Urbana-Champaign
  50. Jan Vykopal (2013). Flow-based Brute-force Attack Detection in Large and High-speed Networks.
  51. Kremer, Hardy (2013). Mining and similarity search in temporal databases. Aachen, Techn. Hochsch., Diss., 2013
  52. 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
  53. Ronald, N (2013). Workers, adventurers, explorers: uncovering activity patterns in Melbourne. Australasian Transport Research Forum (ATRF), 36th, 2013, Brisbane, Queensland, Australia
  54. 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)
  55. Ting, Kai M (2013). Second Generation of Mass Estimation. MONASH UNIV CHURCHILL (AUSTRALIA) GIPPSLAND SCHOOL OF INFORMATION TECHNOLOGY
  56. Vykopal, Jan (2013). SimFlow - a similarity-based detection of brute-force attacks.
  57. Zimmermann, Albrecht (2013). Feature construction based on class outliers. CW Reports

2012

  1. Arthur Zimek, Erich Schubert, and Hans-Peter Kriegel (2012). A survey on unsupervised outlier detection in high-dimensional numerical data. Statistical Analysis and Data Mining: The ASA Data Science Journal 5 5(5), 363-387, Wiley Subscription Services, Inc., A Wiley Company, 10.1002/sam.11161, BibTeX
  2. Hans-Peter Kriegel, Peer Kröger, and Arthur Zimek (2012). Subspace clustering. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 4 2(4), 351-364, John Wiley & Sons, Inc. 10.1002/widm.1057, BibTeX
  3. 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 Berlin Heidelberg, 10.1007/978-3-642-23166-7_1
  4. 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. Database Systems for Advanced Applications, 309-313, Springer Berlin Heidelberg, 10.1007/978-3-642-29035-0_27, BibTeX
  5. Ira Assent, Philipp Kranen, Corinna Baldauf, and Thomas Seidl (2012). AnyOut: Anytime Outlier Detection on Streaming Data. Database Systems for Advanced Applications, 228-242, Springer Berlin Heidelberg, 10.1007/978-3-642-29038-1_18, BibTeX
  6. 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 Models and Languages, 230-244, Springer Berlin Heidelberg, 10.1007/978-3-642-30829-1_16, BibTeX
  7. Emmanuel Müller, Fabian Keller, Sebastian Blanc, and Klemens Böhm (2012). OutRules: A Framework for Outlier Descriptions in Multiple Context Spaces. Machine Learning and Knowledge Discovery in Databases, 828-832, Springer Berlin Heidelberg, 10.1007/978-3-642-33486-3_57, BibTeX
  8. Mohamed Bouguessa (2012). Modeling Outlier Score Distributions. Advanced Data Mining and Applications, 713-725, Springer Berlin Heidelberg, 10.1007/978-3-642-35527-1_59, BibTeX
  9. 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 & Knowledge Engineering 75, 78-98, Elsevier BV, 10.1016/j.datak.2012.03.005, BibTeX
  10. Elke Achtert, Sascha Goldhofer, Hans-Peter Kriegel, Erich Schubert, and Arthur Zimek (2012). Evaluation of Clusterings - Metrics and Visual Support. Data Engineering (ICDE), 2012 IEEE 28th International Conference on, 1285-1288, IEEE, 10.1109/ICDE.2012.128, BibTeX
  11. Hans-Peter Kriegel, Peer Kröger, Erich Schubert, and Arthur Zimek (2012). Outlier Detection in Arbitrarily Oriented Subspaces. Data Mining (ICDM), 2012 IEEE 12th International Conference on, 379-388, IEEE, 10.1109/ICDM.2012.21, BibTeX
  12. Mohamed Bouguessa (2012). A Probabilistic Combination Approach to Improve Outlier Detection. Tools with Artificial Intelligence (ICTAI), 2012 IEEE 24th International Conference on 1, 666-673, IEEE, 10.1109/ICTAI.2012.95, BibTeX
  13. Mandal, Mrinal, and Mukhopadhyay, Amit (2012). Identifying most relevant non-redundant gene markers from gene expression data using PSO-based graph -theoretic approach. Parallel Distributed and Grid Computing (PDGC), 2012 2nd IEEE International Conference on, 374-379, IEEE, 10.1109/PDGC.2012.6449849
  14. Erich Schubert, Remigius Wojdanowski, Arthur Zimek, and Hans-Peter Kriegel (2012). On Evaluation of Outlier Rankings and Outlier Scores. Proceedings of the 2012 SIAM International Conference on Data Mining, 1047-1058, Society for Industrial & Applied Mathematics (SIAM), 10.1137/1.9781611972825.90, BibTeX
  15. Thomas Bernecker, Franz Graf, Hans-Peter Kriegel, Nepomuk Seiler, Christoph Türmer, and Dieter Dill (2012). Knowing: a generic data analysis application. Proceedings of the 15th International Conference on Extending Database Technology, 630-633, ACM, 10.1145/2247596.2247683, BibTeX
  16. Stephan Günnemann, Ines Färber, Kittipat Virochsiri, and Thomas Seidl (2012). Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data. Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, 352-360, ACM, 10.1145/2339530.2339588, BibTeX
  17. Linda Dib, and Alessandra Carbone (2012). CLAG: an unsupervised non hierarchical clustering algorithm handling biological data. BMC Bioinformatics 13(1), 194, BioMed Central Ltd, 10.1186/1471-2105-13-194, BibTeX
  18. Tavares, Bruno (2012). Sistema de recomendação para plataformas de e-learning. Instituto Politécnico do Porto. Instituto Superior de Engenharia do Porto, 10400.22/2601
  19. Suchandt, Steffen, and Runge, Hartmut (2012). Along-track interferometry using TanDEM-X: First results from marine and land applications. Synthetic Aperture Radar, 2012. EUSAR. 9th European Conference on, 392-395, VDE, 978-3-8007-3404-7
  20. Thomas Bernecker (2012). Similarity processing in multi-observation data. 1-253, Ludwig-Maximilians-Universität München, BibTeX
  21. Franz Graf (2012). Data and knowledge engineering for medical image and sensor data. 1-221, Ludwig-Maximilians-Universität München, BibTeX
  22. Ehlers, Jens (2012). Self-Adaptive Performance Monitoring for Component-Based Software Systems. 252, Books on Demand GmbH
  23. Γρίβας, Νικόλαος Δ., and Grivas, Nikolaos D. (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 Interdisciplinary Reviews: Data Mining and Knowledge Discovery 3 1(3), 231-240, John Wiley & Sons, Inc. 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. 12th International Symposium on Spatial and Temporal Databases, 422-440, Springer Berlin Heidelberg, 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. 12th International Symposium on Spatial and Temporal Databases, 512-516, Springer Berlin Heidelberg, 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. Knowledge and Information Systems 3 28(3), 709-733, Springer-Verlag, 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. Data Mining (ICDM), 2011 IEEE 11th International Conference on, 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. Proceedings of the 2011 SIAM International Conference on Data Mining, 13-24, Society for Industrial & Applied Mathematics (SIAM), 10.1137/1.9781611972818.2, BibTeX
  7. Claudia Plant (2011). SONAR: Signal De-mixing for Robust Correlation Clustering. Proceedings of the 2011 SIAM International Conference on Data Mining, 319-330, Society for Industrial & Applied Mathematics (SIAM), 10.1137/1.9781611972818.28, BibTeX
  8. Ivanescu, Anca Maria, Albin, Thivaharan, Abel, Dirk, and Seidl, Thomas (2011). Employing correlation clustering for the identification of piecewise affine models. Proceedings of the 2011 workshop on Knowledge discovery, modeling and simulation, 7-14, ACM, 10.1145/2023568.2023575
  9. Günnemann, Stephan, Kremer, Hardy, and Seidl, Thomas (2011). An extension of the PMML standard to subspace clustering models. Proceedings of the 2011 workshop on Predictive markup language modeling, 48-53, ACM, 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, 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 de Toulouse, BibTeX
  14. MAZEL, Johan (2011). Détection non-supervisée d’anomalies du trafic réseau. 130

2010

  1. Elke Achtert, Hans-Peter Kriegel, Lisa Reichert, Erich Schubert, Remigius Wojdanowski, and Arthur Zimek (2010). Visual Evaluation of Outlier Detection Models. Database Systems for Advanced Applications, 396-399, Springer Berlin Heidelberg, 10.1007/978-3-642-12098-5_34, BibTeX
  2. 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. Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on, 136-141, IEEE, 10.1109/ISDA.2010.5687276, BibTeX
  3. 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. Visual Analytics Science and Technology (VAST), 2010 IEEE Symposium on, 35-42, IEEE, 10.1109/VAST.2010.5652450, BibTeX
  4. Tobias Emrich, Hans-Peter Kriegel, Peer Kröger, Matthias Renz, and Andreas Züfle (2010). Boosting spatial pruning: on optimal pruning of MBRs. Proceedings of the 2010 ACM SIGMOD International Conference on Management of data, 39-50, ACM, 10.1145/1807167.1807174, BibTeX
  5. Kai Ming Ting, Guang-Tong Zhou, Fei Tony Liu, and James Swee Chuan Tan (2010). Mass estimation and its applications. Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, 989-998, ACM, 10.1145/1835804.1835929, BibTeX
  6. Tobias Emrich, Franz Graf, Hans-Peter Kriegel, Matthias Schubert, and Marisa Thoma (2010). On the impact of flash SSDs on spatial indexing. Proceedings of the Sixth International Workshop on Data Management on New Hardware, 3-8, ACM, 10.1145/1869389.1869390, BibTeX
  7. 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. 6 19, 849-875, BibTeX

2009

  1. Hans-Peter Kriegel, Peer Kröger, Erich Schubert, and Arthur Zimek (2009). Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data. Advances in Knowledge Discovery and Data Mining, 831-838, Springer Berlin Heidelberg, 10.1007/978-3-642-01307-2_86, BibTeX
  2. Nikos Mamoulis, Thomas Seidl, Torben Bach Pedersen, Kristian Torp, and Ira Assent (2009). Advances in Spatial and Temporal Databases, 11th International Symposium, SSTD 2009, Aalborg, Denmark, July 8-10, 2009, Proceedings. Lecture Notes in Computer Science 5644, Springer, 10.1007/978-3-642-02982-0, BibTeX
  3. 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. Advances in Spatial and Temporal Databases, 436-440, Springer Berlin Heidelberg, 10.1007/978-3-642-02982-0_35, BibTeX
  4. Gabriela Moise, Arthur Zimek, Peer Kröger, Hans-Peter Kriegel, and Jörg Sander (2009). Subspace and projected clustering: experimental evaluation and analysis. Knowledge and Information Systems 3 21(3), 299-326, Springer-Verlag, 10.1007/s10115-009-0226-y, BibTeX
  5. 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 Transactions on Knowledge Discovery from Data (TKDD) 1 3(1), 1:1-1:58, ACM, 10.1145/1497577.1497578, BibTeX
  6. Hans-Peter Kriegel, Peer Kröger, Erich Schubert, and Arthur Zimek (2009). LoOP: local outlier probabilities. Proceedings of the 18th ACM conference on Information and knowledge management, 1649-1652, ACM, 10.1145/1645953.1646195, BibTeX
  7. Arthur Zimek (2009). Correlation clustering. ACM SIGKDD Explorations Newsletter 1 11(1), 53-54, ACM, 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. Scientific and Statistical Database Management, 580-585, Springer Berlin Heidelberg, 10.1007/978-3-540-69497-7_41, BibTeX

Google Scholar

Papers that cite ELKI releases can be found using google scholar:

Release 0.1: http://scholar.google.de/scholar?cites=947308291279715946

Release 0.2: http://scholar.google.de/scholar?cites=7259117758981814570

Release 0.3: http://scholar.google.de/scholar?cites=318410196722457623

Release 0.4: http://scholar.google.de/scholar?cites=13815677342913404474

Release 0.5: http://scholar.google.de/scholar?cites=6974576405934743829

Release 0.6: http://scholar.google.de/scholar?cites=10964489485233751703

Release 0.7: http://scholar.google.de/scholar?cites=13946522890235188309