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List of Publications
2024 |
|
| [142] | Philipp Röchner, Henrique O. Marques, Ricardo J. G. B. Campello, Arthur Zimek:
Evaluating outlier probabilities: assessing sharpness, refinement, and calibration using stratified and weighted measures Data Mining and Knowledge Discovery, 38(6), 3719-3757, 2024. [ EE (Springer) ] |
| [141] | Muhammad Rajabinasab, Anton Danholt Lautrup, Tobias Hyrup, Arthur Zimek:
A Dynamic Evaluation Metric for Feature Selection Proceedings of the 17th International Conference on Similarity Search and Applications (SISAP), Providence, RI, USA, pp. 65-72, 2024. |
| [140] | Camilla Birch Okkels, Martin Aumüller, Arthur Zimek:
On the Design of Scalable Outlier Detection Methods Using Approximate Nearest Neighbor Graphs Proceedings of the 17th International Conference on Similarity Search and Applications (SISAP), Providence, RI, USA, pp. 170-184, 2024. |
| [139] | Philipp Röchner, Henrique O. Marques, Ricardo J. G. B. Campello, Arthur Zimek, Franz Rothlauf:
Robust Statistical Scaling of Outlier Scores: Improving the Quality of Outlier Probabilities for Outliers Proceedings of the 17th International Conference on Similarity Search and Applications (SISAP), Providence, RI, USA, pp. 215-222, 2024. |
| [138] | Yi Cai, Arthur Zimek, Eirini Ntoutsi, Gerhard Wunder:
Transparent Neighborhood Approximation for Text Classifier Explanation by Probability-Based Editing Proceedings of the 11th IEEE International Conference on Data Science and Advanced Analytics (DSAA), San Diego, CA, USA, pp. 1-10, 2024. |
2023 |
|
| [137] | Michael E. Houle, Marie Kiermeier, Arthur Zimek:
Clustering High-Dimensional Data In: Rokach, L., Maimon, O., Shmueli, E. (eds) Machine Learning for Data Science Handbook. Data Mining and Knowledge Discovery Handbook, 3rd edition, Springer, 2023. [ EE (springerlink) ] |
| [136] | Henrique O. Marques, Lorne Swersky, Jörg Sander, Ricardo J. G. B. Campello, Arthur Zimek:
On the evaluation of outlier detection and one-class classification: a comparative study of algorithms, model selection, and ensembles Data Mining and Knowledge Discovery, 37(4), 1473-1517, 2023. [ EE (Springer) ] |
| [135] | Félix Iglesias, Tanja Zseby, Alexander Hartl, Arthur Zimek:
SDOclust: Clustering with Sparse Data Observers Proceedings of the 16th International Conference on Similarity Search and Applications (SISAP), A Coruña, Spain, pp. 185-199, 2023. |
| [134] | Félix Iglesias, Alexander Hartl, Tanja Zseby, Arthur Zimek:
Anomaly detection in streaming data: A comparison and evaluation study Expert Systems with Applications, 233: 120994, 2023. |
2022 |
|
| [133] | Conor McCarthy, Panagiotis Tampakis, Marco Chiarandini, Morten Bredsgaard Randers, Stefan Jänicke, Arthur Zimek:
Analyzing Passing Sequences for the Prediction of Goal-Scoring Opportunities MLSA@PKDD/ECML 2022: 27-40, 2022. |
| [132] | Henrique O. Marques, Arthur Zimek, Ricardo J. G. B. Campello, Jörg Sander:
Similarity-Based Unsupervised Evaluation of Outlier Detection Proceedings of the 15th International Conference on Similarity Search and Applications (SISAP), Bologna, Italy, pp. 234-248, 2022. |
| [131] | Rui Zhang, Arthur Zimek, Peter Schneider-Kamp:
A Simple Meta-path-free Framework for Heterogeneous Network Embedding Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), Atlanta, Georgia, USA, 2022. |
| [130] | Rui Zhang, Arthur Zimek, Peter Schneider-Kamp:
Unsupervised Representation Learning on Attributed Multiplex Network Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), Atlanta, Georgia, USA, 2022. |
| [129] | Yi Cai, Arthur Zimek, Gerhard Wunder, Eirini Ntoutsi:
Power of Explanations: Towards automatic debiasing in hate speech detection Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics (DSAA), Shenzhen, China, 2022. |
| [128] | Erik Andersen, Marco Chiarandini, Marwan Hassani, Stefan Jänicke, Panagiotis Tampakis, Arthur Zimek:
Evaluation of Probability Distribution Distance Metrics in Traffic Flow Outlier Detection Proceedings of the 23rd IEEE International Conference on Mobile Data Management (MDM 2022), Paphos, Cyprus, pp. 64-69, 2022. [ EE (IEEE) ] |
2021 |
|
| [127] | Félix Iglesias, Tanja Zseby, Arthur Zimek:
Clustering refinement International Journal of Data Science and Analytics 12(4): 333-353, 2021. |
| [126] | Yi Cai, Arthur Zimek, Eirini Ntoutsi:
XPROAX - Local explanations for text classification with progressive neighborhood approximation Proceedings of the 8th IEEE International Conference on Data Science and Advanced Analytics (DSAA), Porto, Portugal, 2021. |
| [125] | Nicklas Sindlev Andersen, Marco Chiarandini, Stefan Jänicke, Panagiotis Tampakis, Arthur Zimek:
Detecting Wandering Behavior of People with Dementia Proceedings of the 2021 International Conference on Data Mining, ICDM 2021 - Workshops, Auckland, New Zealand (ICDM Workshops), pp. 727-733, 2021. |
| [124] | Jonatan Møller Nuutinen Gøttcke, Arthur Zimek, Ricardo J. G. B. Campello:
Non-parametric Semi-supervised Learning by Bayesian Label Distribution Propagation Proceedings of the 14th International Conference on Similarity Search and Applications (SISAP), pp. 118-132, 2021. |
| [123] | Jonatan Møller Nuutinen Gøttcke, Arthur Zimek:
Handling Class Imbalance in k-Nearest Neighbor Classification by Balancing Prior Probabilities Proceedings of the 14th International Conference on Similarity Search and Applications (SISAP), pp. 247-261, 2021. |
2020 |
|
| [122] | Félix Iglesias Vázquez, Tanja Zseby, Arthur Zimek:
Interpretability and Refinement of Clustering 7th IEEE International Conference on Data Science and Advanced Analytics (DSAA), Sydney, Australia, pp. 21-29, 2020. [ EE (IEEE) ] |
| [121] | Rui Zhang, Maéva Vignes, Ulrich Steiner, Arthur Zimek:
Matching Research Publications to the United Nations’ Sustainable Development Goals by Multi-Label-Learning with Hierarchical Categories 7th IEEE International Conference on Data Science and Advanced Analytics (DSAA), Sydney, Australia, pp. 516-525, 2020. [ EE (IEEE) ] |
| [120] | Jonas Herskind Sejr, Arthur Zimek, Peter Schneider-Kamp:
Explainable Detection of Zero Day Web Attacks 3rd International Conference on Data Intelligence and Security (ICDIS), pp. 71-78, 2020. |
| [119] | Irena Koprinska, Michael Kamp, Annalisa Appice, Corrado Loglisci, Luiza Antonie, Albrecht Zimmermann, Riccardo Guidotti, Özlem Özgöbek, Rita P. Ribeiro, Ricard Gavaldà, João Gama, Linara Adilova, Yamuna Krishnamurthy, Pedro M. Ferreira, Donato Malerba, Ibéria Medeiros, Michelangelo Ceci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras, Peter Christen, Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Anna Monreale, Przemyslaw Biecek, Salvatore Rinzivillo, Benjamin Kille, Andreas Lommatzsch, Jon Atle Gulla:
Proceedings of the ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020 Ghent, Belgium, September 14-18, 2020 (Communications in Computer and Information Science 1323, Springer), 2020. |
| [118] | Shin'ichi Satoh, Lucia Vadicamo, Arthur Zimek, Fabio Carrara, Ilaria Bartolini, Martin Aumüller, Björn Þór Jónsson, Rasmus Pagh:
Proceedings of the 13th International Conference on Similarity Search and Applications (SISAP 2020) Copenhagen, Denmark, September 30 -- October 2, 2020 (Lecture Notes in Computer Science 12440, Springer), 2020. [ EE (Springer) | conference webpage ] |
| [117] | Félix Iglesias, Tanja Zseby, Arthur Zimek:
Absolute Cluster Validity IEEE Trans. Pattern Anal. Mach. Intell. 42(9): 2096-2112, 2020. [ EE (IEEE) ] |
| [116] | Henrique O. Marques, Ricardo J. G. B Campello, Jörg Sander, Arthur Zimek:
Internal Evaluation of Unsupervised Outlier Detection ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 14, Issue 4 (June 2020), Article No. 47, pp. 1-42, 2020. [ EE (ACM) ] |
| [115] | Ricardo J. G. B. Campello, Peer Kröger, Jörg Sander, Arthur Zimek:
Density-based clustering Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 10 (2), 2020. [ EE (Wiley) ] |
| [114] | Rui Zhang, Peter Schneider-Kamp, Arthur Zimek:
Improving Semantic Similarity of Words by Retrofitting Word Vectors in Sense Level Proceedings ICAART (2), pp. 108-119, 2020. [ EE ] |
2019 |
|
| [113] | Félix Iglesias, Tanja Zseby, Daniel C. Ferreira, Arthur Zimek:
MDCGen: Multidimensional Dataset Generator for Clustering J. Classification 36(3): 599-618, 2019. [ EE (Springer) ] |
| [112] | Félix Iglesias Vázquez, Alexander Hartl, Tanja Zseby, Arthur Zimek:
Are Network Attacks Outliers? A Study of Space Representations and Unsupervised Algorithms PKDD/ECML Workshops (2) 2019: 159-175, 2019. [ EE (Springer) ] |
| [111] | Jadson Castro Gertrudes, Arthur Zimek, Jörg Sander, Ricardo J. G. B. Campello:
A unified view of density-based methods for semi-supervised clustering and classification Data Mining and Knowledge Discovery, 33(6), 1894-1952, 2019. [ EE (Springer) ] |
| [110] | Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Albrecht Zimmermann:
1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2019) Proceedings of the 1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML), pp. 1-3 (editorial), 2019. [ EE (CEUR) | workshop webpage ] |
| [109] | Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Albrecht Zimmermann:
Proceedings of the 1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML) co-located with SIAM International Conference on Data Mining (SDM 2019), Calgary, AB, Canada, 2019. [ EE (CEUR) | workshop webpage ] |
| [108] | Guilherme O. Campos, Edré Moreira, Wagner Meira Jr., Arthur Zimek:
Outlier detection in graphs: A study on the impact of multiple graph models Comput. Sci. Inf. Syst. 16(2): 565-595, 2019. [ EE ] |
| [107] | Ruben Becker, Imane Hafnaoui, Michael E. Houle, Pan Li, Arthur Zimek:
Subspace Determination through Local Intrinsic Dimensional Decomposition Proceedings of the 12th International Conference on Similarity Search and Applications (SISAP), Newark, NJ, pp. 281-289, 2019. [ EE (springer) ] |
| [106] | Ruben Becker, Imane Hafnaoui, Michael E. Houle, Pan Li, Arthur Zimek:
Subspace Determination through Local Intrinsic Dimensional Decomposition: Theory and Experimentation CoRR abs/1907.06771, 2019. [ EE (arxiv) ] |
| [105] | Erich Schubert, Arthur Zimek:
ELKI: A large open-source library for data analysis - ELKI Release 0.7.5 "Heidelberg" CoRR abs/1902.03616, 2019. [ EE (arxiv) ] |
2018 |
|
| [104] | Youcef Djenouri, Arthur Zimek, Marco Chiarandini:
Outlier Detection in Urban Traffic Flow Distributions Proceedings of the 18 IEEE International Conference on Data Mining, Singapore, Singapore, pp. 935-940, 2018. [ EE (IEEE) ] |
| [103] | Félix Iglesias Vázquez, Tanja Zseby, Arthur Zimek:
Outlier Detection Based on Low Density Models Proceedings of the IEEE International Conference on Data Mining Workshops, ICDM Workshops, Singapore, Singapore, pp. 970-979, 2018. [ EE (IEEE) ] |
| [102] | Michael E. Houle, Erich Schubert, Arthur Zimek:
On the Correlation Between Local Intrinsic Dimensionality and Outlierness Proceedings of the 11th International Conference on Similarity Search and Applications (SISAP), Lima, Peru, pp. 177-191, 2018. [ EE (springerlink) ] |
| [101] | Arthur Zimek, Peter Filzmoser:
There and Back Again: Outlier Detection Between Statistical Reasoning And Data Mining Algorithms Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 8 (6): e1280, 2018. [ EE (Wiley) ] |
| [100] | Guilherme O. Campos, Wagner Meira Jr., Arthur Zimek:
Outlier Detection in Graphs: On the Impact of Multiple Graph Models Proceedings of the 8th International Conference on Web Intelligence, Mining and Semantics (WIMS), Novi Sad, Serbia, pp. 21:1-21:12, 2018. [ EE (ACM) ] |
| [99] | Youcef Djenouri, Arthur Zimek:
Outlier Detection in Urban Traffic Data Proceedings of the 8th International Conference on Web Intelligence, Mining and Semantics (WIMS), Novi Sad, Serbia, pp. 3:1-3:12, 2018. [ EE (ACM) ] |
| [98] | Jadson Castro Gertrudes, Arthur Zimek, Jörg Sander, Ricardo J. G. B. Campello:
A unified framework of density-based clustering for semi-supervised classification Proceedings of the 30th International Conference on Scientific and Statistical Database Management (SSDBM), Bozen-Bolzano, Italy, pp. 11:1-11:12, 2018. [ EE (ACM) ] |
| [97] | Guilherme O. Campos, Arthur Zimek, Wagner Meira Jr.:
An Unsupervised Boosting Strategy for Outlier Detection Ensembles Proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD), Melbourne, VIC, Australia, Part I, pp. 564-576, 2018. [ EE (springerlink) ] |
| [96] | Peer Kroeger, Arthur Zimek:
Subspace Clustering Techniques In L. Liu and M. Tamer Özsu (eds.): Encyclopedia of Database Systems, 2nd edition, Springer, 2018. [ EE (springerlink) ] |
| [95] | Arthur Zimek, Erich Schubert:
Outlier Detection In L. Liu and M. Tamer Özsu (eds.): Encyclopedia of Database Systems, 2nd edition, Springer, 2018. [ EE (springerlink) ] |
2017 |
|
| [94] | Evelyn Kirner, Erich Schubert, Arthur Zimek:
Good and Bad Neighborhood Approximations for Outlier Detection Ensembles Proceedings of the 10th International Conference on Similarity Search and Applications (SISAP), Munich, Germany, pp. 173-187, 2017. [ EE (springerlink) ] |
| [93] | Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
The (black) art of runtime evaluation: Are we comparing algorithms or implementations? Knowledge and Information Systems, 52(2), pp. 341-378, 2017. [ EE (springerlink) | EE (springer nature read cube) ] |
| [92] | Guillaume Casanova, Elias Englmeier, Michael Houle, Peer Kroeger, Michael Nett, Erich Schubert, Arthur Zimek:
Dimensional Testing for Reverse k-Nearest Neighbor Search Proceedings of the VLDB Endowment, 10(7), pp. 769-780, 2017. [ EE (VLDB) | EE (ACM) ] |
| [91] | Daniel Basaran, Eirini Ntoutsi, Arthur Zimek:
Redundancies in Data and their Effect on the Evaluation of Recommendation Systems: A Case Study on the Amazon Reviews Datasets Proceedings of the 2017 SIAM International Conference on Data Mining (SDM), Houston, TX, 2017. [ preprint (pdf) | EE (SIAM) ] |
2016 |
|
| [90] | Lorne Swersky, Henrique O. Marques, Jörg Sander, Ricardo J. G. B. Campello, Arthur Zimek:
On the Evaluation of Outlier Detection and One-Class Classification Methods Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), Montreal, QB, 2016. [ EE (IEEE) ] |
| [89] | Guilherme O. Campos, Arthur Zimek, Jörg Sander, Ricardo J. G. B. Campello, Barbora Micenková, Erich Schubert, Ira Assent, Michael E. Houle:
On the Evaluation of Unsupervised Outlier Detection: Measures, Datasets, and an Empirical Study Continued [Abstract] Proceedings of the LWDA 2016 Workshops: KDML, FGWM, FGIR, and FGDB, Potsdam, Germany, p. 234, 2016. [ EE (CEUR) | supplementary material ] |
| [88] | Ira Assent, Carlotta Domeniconi, Francesco Gullo, Andrea Tagarelli, Arthur Zimek:
MultiClust 2013: Multiple Clusterings, Multi-view Data, and Multi-source Knowledge-driven Clustering [Workshop Report] SIGKDD Explorations, Volume 18, Issue 1 (June 2016), pp. 35-38, 2016. [ EE (ACM) ] |
| [87] | Guilherme O. Campos, Arthur Zimek, Jörg Sander, Ricardo J. G. B. Campello, Barbora Micenková, Erich Schubert, Ira Assent, Michael E. Houle:
On the Evaluation of Unsupervised Outlier Detection: Measures, Datasets, and an Empirical Study Data Mining and Knowledge Discovery, 30(4), pp. 891-927, 2016. 
[ EE (springerlink) | supplementary material ] |
| [86] | Pablo A. Jaskowiak, Davoud Moulavi, Antonio C. S. Furtado, Ricardo J. G. B. Campello, Arthur Zimek, Jörg Sander:
On strategies for building effective ensembles of relative clustering validity criteria Knowledge and Information Systems, 47(2), pp. 329-354, 2016. [ EE (springerlink) ] |
2015 |
|
| [85] | Erich Schubert, Michael Weiler, Arthur Zimek:
Outlier Detection and Trend Detection: Two Sides of the Same Coin ICDM Workshops 2015, pp. 40-46, 2015. [ EE (IEEE) ] |
| [84] | Erich Schubert, Alexander Koos, Tobias Emrich, Andreas Züfle, Klaus A. Schmid, Arthur Zimek:
A Framework for Clustering Uncertain Data Proceedings of the VLDB Endowment, 8(12), pp. 1976-1979, 2015. [ ELKI software presentation (webpage) | EE (VLDB) | EE (ACM) ] |
| [83] | Ricardo J. G. B. Campello, Davoud Moulavi, Arthur Zimek, Jörg Sander:
Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 10, Issue 1 (July 2015), Article No. 5, pp. 1-51, 2015. [ EE (ACM) | synthetic data with noise (archive) | synthetic data (archive) without noise: see [67]) ] |
| [82] | Henrique O. Marques, Ricardo J. G. B. Campello, Arthur Zimek, Jörg Sander:
On the internal evaluation of unsupervised outlier detection Proceedings of the 27th International Conference on Scientific and Statistical Database Management (SSDBM), San Diego, CA, 2015. [ EE (ACM) ] |
| [81] | Erich Schubert, Arthur Zimek, Hans-Peter Kriegel:
Fast and Scalable Outlier Detection with Approximate Nearest Neighbor Ensembles Proceedings of the 20th International Conference on Database Systems for Advanced Applications (DASFAA), Hanoi, Vietnam, 2015. [ EE (springerlink) ] |
| [80] | Arthur Zimek, Jilles Vreeken:
The blind men and the elephant: on meeting the problem of multiple truths in data from clustering and pattern mining perspectives Machine Learning, Volume 98, Issue 1-2, pp. 121-155, DOI: 10.1007/s10994-013-5334-y, 2015. [ EE (springerlink) ] |
2014 |
|
| [79] | Arthur Zimek, Ira Assent, Jilles Vreeken:
Frequent Pattern Mining Algorithms for Data Clustering in C. C. Aggarwal, C. K. Reddy (ed.): Frequent Pattern Mining, Springer: 403-423, 2014. [ EE (Springer) ] |
| [78] | Andreas Züfle, Tobias Emrich, Klaus A. Schmid, Nikos Mamoulis, Arthur Zimek, Matthias Renz:
Representative Clustering of Uncertain Data Proceedings of the 20th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), New York, NY, 2014. [ EE (ACM) ] |
| [77] | Arthur Zimek, Ricardo J. G. B. Campello, Jörg Sander:
Data Perturbation for Outlier Detection Ensembles Proceedings of the 26th International Conference on Scientific and Statistical Database Management (SSDBM), Aalborg, Denmark, 2014. [ preprint (pdf) ] |
| [76] | Jundong Li, Jörg Sander, Ricardo J. G. B. Campello, Arthur Zimek:
Active Learning Strategies for Semi-Supervised DBSCAN Canadian Conference on AI, 179-190, 2014. [ EE (springer) ] |
| [75] | Davoud Moulavi, Pablo A. Jaskowiak, Ricardo J. G. B. Campello, Arthur Zimek, Jörg Sander:
Density-based Clustering Validation Proceedings of the 14th SIAM International Conference on Data Mining (SDM), Philadelphia, PA, 2014. [ preprint (pdf) | code archive (matlab) ] |
| [74] | Erich Schubert, Arthur Zimek, Hans-Peter Kriegel:
Generalized Outlier Detection with Flexible Kernel Density Estimates Proceedings of the 14th SIAM International Conference on Data Mining (SDM), Philadelphia, PA, 2014. [ preprint (pdf) ] |
| [73] | Mojgan Pourrajabi, Davoud Moulavi, Ricardo J. G. B. Campello, Arthur Zimek, Jörg Sander, Randy Goebel:
Model Selection for Semi-Supervised Clustering Proceedings of the 17th International Conference on Extending Database Technology (EDBT), Athens, Greece, 2014. [ preprint (pdf) ] |
| [72] | Erich Schubert, Arthur Zimek, Hans-Peter Kriegel:
Local outlier detection reconsidered: a generalized view on locality with applications to spatial, video, and network outlier detection Data Mining and Knowledge Discovery, Volume 28, Number 1 / January 2014, pp. 190-237, DOI: 10.1007/s10618-012-0300-z, 2014. [ EE (springer) ] |
| [71] | Xuan Hong Dang, Ira Assent, Raymond T. Ng, Arthur Zimek, Erich Schubert:
Discriminative Features for Identifying and Interpreting Outliers Proceedings of the 30th International Conference on Data Engineering (ICDE), Chicago, IL, 2014. [ preprint (pdf) ] |
2013 |
|
| [70] | Arthur Zimek, Ricardo J. G. B. Campello, Jörg Sander:
Ensembles for Unsupervised Outlier Detection: Challenges and Research Questions SIGKDD Explorations, Volume 15, Issue 1 (June 2013), pp. 11-22, 2013. [ EE (ACM) ] |
| [69] | Arthur Zimek:
Clustering High-Dimensional Data in C. C. Aggarwal, C. K. Reddy (ed.): Data Clustering: Algorithms and Applications, CRC Press: 201–230, 2013. |
| [68] | Ira Assent, Carlotta Domeniconi, Francesco Gullo, Andrea Tagarelli, Arthur Zimek (editors):
4th MultiClust Workshop on Multiple Clusterings, Multi-view Data, and Multi-source Knowledge-driven Clustering in conjunction with the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 11-14 2013, Chicago, Illinois, USA, 2013. [ workshop webpage | EE (ACM) ] |
| [67] | Arthur Zimek, Matthew Gaudet, Ricardo J. G. B. Campello, Jörg Sander:
Subsampling for Efficient and Effective Unsupervised Outlier Detection Ensembles Proceedings of the 19th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), Chicago, IL, 2013. [ paper (pdf) | EE (ACM) | slides (pdf) | poster (pdf) | synthetic data (archive) ] |
| [66] | Erich Schubert, Arthur Zimek, Hans-Peter Kriegel:
Geodetic Distance Queries on R-Trees for Indexing Geographic Data Proc. 13th International Symposium on Spatial and Temporal Databases (SSTD), Munich, Germany, 2013. [ EE (springer) ] |
| [65] | Elke Achtert, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
Interactive Data Mining with 3D-Parallel-Coordinate-Trees Proceedings of the 2013 ACM SIGMOD New York, NY, 2013. [ EE (ACM) | ELKI software presentation (webpage) ] |
| [64] | Arthur Zimek, Erich Schubert, Hans-Peter Kriegel:
Outlier Detection in High-Dimensional Data Tutorial at the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Gold Coast, Australia, 2013. [ tutorial slides | tutorial webpage ] |
| [63] | Ricardo J. G. B. Campello, Davoud Moulavi, Arthur Zimek, Jörg Sander:
A framework for semi-supervised and unsupervised optimal extraction of clusters from hierarchies Data Mining and Knowledge Discovery, Volume 27, Number 3 / November 2013, pp. 344-371, DOI: 10.1007/s10618-013-0311-4, 2013. [ EE (springerlink) ] |
| [62] | Kelvin Sim, Vivekanand Gopalkrishnan, Arthur Zimek, Gao Cong:
A survey on enhanced subspace clustering Data Mining and Knowledge Discovery, Volume 26, Number 2 / March 2013, pp. 332-397, DOI: 10.1007/s10618-012-0258-x, 2013. [ EE (springerlink) ] |
2012 |
|
| [61] | Arthur Zimek, Erich Schubert, Hans-Peter Kriegel:
Outlier Detection in High-Dimensional Data Tutorial at the 12th IEEE International Conference on Data Mining (ICDM), Brussels, Belgium, 2012. [ tutorial slides | tutorial webpage ] |
| [60] | Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
Outlier Detection in Arbitrarily Oriented Subspaces Proceedings of the 12th IEEE International Conference on Data Mining (ICDM), Brussels, Belgium, 2012. [ preprint (pdf) | EE (IEEE) ] |
| [59] | Arthur Zimek, Erich Schubert, Hans-Peter Kriegel:
A Survey on Unsupervised Outlier Detection in High-Dimensional Numerical Data Statistical Analysis and Data Mining 5 (5): 363-387, 2012. [ EE (Wiley) ] |
| [58] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Subspace Clustering Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2 (4): 351--364, 2012. [ EE (Wiley) ] |
| [57] | Emmanuel Müller, Thomas Seidl, Suresh Venkatasubramanian, Arthur Zimek (editors):
3rd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings in conjunction with 2012 SIAM International Conference on Data Mining, April 26-28, 2012, Anaheim, CA, 2012. [ workshop webpage | EE (SIAM) ] |
| [56] | Irene Ntoutsi, Arthur Zimek, Themis Palpanas, Peer Kröger, Hans-Peter Kriegel:
Density-based Projected Clustering over High Dimensional Data Streams Proceedings of the 12th SIAM International Conference on Data Mining (SDM), Anaheim, CA, 2012. [ EE (SIAM) ] |
| [55] | Erich Schubert, Remigius Wojdanowski, Arthur Zimek, Hans-Peter Kriegel:
On Evaluation of Outlier Rankings and Outlier Scores Proceedings of the 12th SIAM International Conference on Data Mining (SDM), Anaheim, CA, 2012. [ preprint (pdf) | EE (SIAM) | abstract ] |
| [54] | Elke Achtert, Sascha Goldhofer, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
Evaluation of Clusterings -- Metrics and Visual Support Proceedings of the 28th International Conference on Data Engineering (ICDE), Washington, DC, 2012. [ preprint (pdf) | EE (IEEE computer society) | ELKI software presentation (webpage) ] |
2011 |
|
| [53] | Hans-Peter Kriegel, Irene Ntoutsi, Myra Spiliopoulou, Grigorios Tsoumakas, Arthur Zimek:
Mining Complex Dynamic Data Tutorial at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Athens, Greece, 2011. [ abstract | webpage ] |
| [52] | Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
Evaluation of Multiple Clustering Solutions Proc. 2nd MultiClust Workshop on Discovering, Summarizing and Using Multiple Clusterings (MultiClust 2011) in conjunction with ECML PKDD, Athens, Greece, 2011. [ preprint (pdf) | EE (CEUR-WS) ] |
| [51] | Jilles Vreeken, Arthur Zimek:
When Pattern Met Subspace Cluster - A Relationship Story Proc. 2nd MultiClust Workshop on Discovering, Summarizing and Using Multiple Clusterings (MultiClust 2011) in conjunction with ECML PKDD, Athens, Greece, 2011. [ preprint (pdf) | EE (CEUR-WS) ] |
| [50] | Thomas Bernecker, Franz Graf, Hans-Peter Kriegel, Christian Mönnig, Arthur Zimek:
BeyOND - Unleashing BOND Proc. 5th International Workshop on Ranking in Databases (DBRank 2011) in conjunction with VLDB, Seattle, WA, 2011. [ supplementary material ] |
| [49] | Elke Achtert, Achmed Hettab, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
Spatial Outlier Detection: Data, Algorithms, Visualizations Proc. 12th International Symposium on Spatial and Temporal Databases (SSTD), Minneapolis, MN, 2011. [ EE (springerlink) | ELKI software presentation (webpage) | Best Demonstration Paper ] |
| [48] | Thomas Bernecker, Michael E. Houle, Hans-Peter Kriegel, Peer Kröger, Matthias Renz, Erich Schubert, Arthur Zimek:
Quality of Similarity Rankings in Time Series Proc. 12th International Symposium on Spatial and Temporal Databases (SSTD), Minneapolis, MN, 2011. [ EE (springerlink) ] |
| [47] | Hans-Peter Kriegel, Peer Kröger, Irene Ntoutsi, Arthur Zimek:
Density-Based Subspace Clustering over Dynamic Data Proc. 23rd International Conference on Scientific and Statistical Database Management (SSDBM), Portland, OR, 2011. [ EE (springerlink) ] |
| [46] | Hans-Peter Kriegel, Peer Kröger, Jörg Sander, Arthur Zimek:
Density-based clustering Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 1 (3): 231-240, 2011. [ EE (Wiley) ] |
| [45] | Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
Interpreting and Unifying Outlier Scores Proceedings of the 11th SIAM International Conference on Data Mining (SDM), Mesa, AZ, 2011. [ preprint (pdf) | EE (SIAM) ] |
2010 |
|
| [44] | Kyoji Kawagoe, Thomas Bernecker, Hans-Peter Kriegel, Matthias Renz, Arthur Zimek, Andreas Züfle:
Similarity Search in Time Series of Dynamical Model-based Systems Proc. 2nd International Workshop on Database Technology for Data Management in Life Sciences and Medicine (DBLM 2010) in conjunction with 21st DEXA 2010: Bilbao, Spain, 2010. [ EE (IEEE) ] |
| [43] | Arthur Zimek, Fabian Buchwald, Eibe Frank, Stefan Kramer:
A Study of Hierarchical and Flat Classification of Proteins IEEE/ACM Transactions on Computational Biology and Bioinformatics, Volume 7, Number 3, pp. 563-571, 2010. [ EE (IEEE) | EE (ACM) | synthetic data (arff) ] |
| [42] | Hans-Peter Kriegel, Peer Kröger, Irene Ntoutsi, Arthur Zimek:
Towards Subspace Clustering on Dynamic Data: An Incremental Version of PreDeCon Proc. 1st International Workshop on Novel Data Stream Pattern Mining Techniques (StreamKDD'10) in conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, 2010. [ EE (ACM) ] |
| [41] | Hans-Peter Kriegel, Arthur Zimek:
Subspace Clustering, Ensemble Clustering, Alternative Clustering, Multiview Clustering: What Can We Learn From Each Other? Proc. 1st International Workshop on Discovering, Summarizing and Using Multiple Clusterings (MultiClust 2010) in conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, 2010. [ paper (pdf) | slides (pdf) ] |
| [40] | Ines Färber, Stephan Günnemann, Hans-Peter Kriegel, Peer Kröger, Emmanuel Müller, Erich Schubert, Thomas Seidl, Arthur Zimek:
On Using Class-Labels in Evaluation of Clusterings Proc. 1st International Workshop on Discovering, Summarizing and Using Multiple Clusterings (MultiClust 2010) in conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, 2010. [ paper (pdf) ] |
| [39] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Outlier Detection Techniques Tutorial at 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, 2010. [ abstract | slides (pdf) ] |
| [38] | Johannes Aßfalg, Jing Gong, Hans-Peter Kriegel, Alexey Pryakhin, Tiandi Wei, Arthur Zimek:
Investigating a Correlation between Subcellular Localization and Fold of Proteins Journal of Universal Computer Science (J.UCS), Volume 16, Issue 5, pp. 604-621, 2010. [ EE (J.UCS) | supplementary material (webpage) ] |
| [37] | Michael E. Houle, Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
Can Shared-Neighbor Distances Defeat the Curse of Dimensionality? Proc. of the 22nd International Conference on Scientific and Statistical Database Management (SSDBM 2010), Heidelberg, Germany, 2010. [ EE (springerlink) | preprint (pdf) | slides (pdf) | supplementary material (webpage) ] |
| [36] | Thomas Bernecker, Tobias Emrich, Franz Graf, Hans-Peter Kriegel, Peer Kröger, Matthias Renz, Erich Schubert, Arthur Zimek:
Subspace Similarity Search: Efficient k-NN Queries in Arbitrary Subspaces Proc. of the 22nd International Conference on Scientific and Statistical Database Management (SSDBM 2010), Heidelberg, Germany, 2010. [ EE (springerlink) | more information ] |
| [35] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Outlier Detection Techniques Tutorial at 10th SIAM International Conference on Data Mining (SDM 2010), Columbus, OH, 2010. [ abstract | slides (pdf) ] |
| [34] | Elke Achtert, Hans-Peter Kriegel, Lisa Reichert, Erich Schubert, Remigius Wojdanowski, Arthur Zimek:
Visual Evaluation of Outlier Detection Models Proc. of the 15th International Conference on Database Systems for Advanced Applications (DASFAA 2010), Tsukuba, Japan, 2010. [ EE (springerlink) | poster (pdf) | ELKI software presentation (webpage) | ELKI software documentation (webpage) ] |
| [33] | Thomas Bernecker, Tobias Emrich, Franz Graf, Hans-Peter Kriegel, Peer Kröger, Matthias Renz, Erich Schubert, Arthur Zimek:
Subspace Similarity Search Using the Ideas of Ranking and Top-k Retrieval Proc. 4th International Workshop on Ranking in Databases (DBRank 2010) in conjunction with IEEE 26th International Conference on Data Engineering (ICDE 2010), Long Beach, California, 2010. [ paper (pdf) | more information ] |
2009 |
|
| [32] | Gabriela Moise, Arthur Zimek, Peer Kröger, Hans-Peter Kriegel, Jörg Sander:
Subspace and Projected Clustering: Experimental Evaluation and Analysis Knowledge and Information Systems 21(3): 299-326, 2009. [ EE (springerlink) | test data (zip-archive, 107 MB) ] |
| [31] | Peer Kröger, Arthur Zimek:
Subspace Clustering Techniques In L. Liu and M. Tamer Özsu (eds.): Encyclopedia of Database Systems, Springer, 2009. [ EE (springerlink) ] |
| [30] | Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
LoOP: Local Outlier Probabilities Proc. 18th ACM Conference on Information and Knowledge Management (CIKM 2009), Hong Kong, China, 2009. [ EE (ACM) ] |
| [29] | Arthur Zimek:
Correlation Clustering SIGKDD Explorations, Volume 11, Issue 1 (July 2009), pp. 53-54, 2009. [ EE (ACM) ] |
| [28] | Elke Achtert, Thomas Bernecker, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
ELKI in Time: ELKI 0.2 for the Performance Evaluation of Distance Measures for Time Series 11th International Symposium on Spatial and Temporal Databases (SSTD 2009), Aalborg, Denmark, 2009. [ EE (springerlink) | paper (pdf) | poster (pdf) | ELKI software presentation (webpage) | ELKI software documentation (webpage) ] |
| [27] | Johannes Aßfalg, Jing Gong, Hans-Peter Kriegel, Alexey Pryakhin, Tiandi Wei, Arthur Zimek:
Supervised Ensembles of Prediction Methods for Subcellular Localization Journal of Bioinformatics and Computational Biology (JBCB), Volume 7, Issue 2 (April 2009), pp. 269-285, 2009. [ EE (World Scientific) | prediction server ] |
| [26] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Outlier Detection Techniques Tutorial at the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2009), Bangkok, Thailand, 2009. [ slides (pdf) ] |
| [25] | Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data Proc. 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2009), Bangkok, Thailand, 2009. [ EE (springerlink) | paper (pdf) | slides (pdf) ] |
| [24] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Clustering High Dimensional Data: A Survey on Subspace Clustering, Pattern-based Clustering, and Correlation Clustering ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 3, Issue 1 (March 2009), Article No. 1, pp. 1-58, 2009. [ EE (ACM) ] |
2008 |
|
| [23] | Elke Achtert, Christian Böhm, Jörn David, Peer Kröger, Arthur Zimek:
Global Correlation Clustering Based on the Hough Transform Statistical Analysis and Data Mining, Volume 1, Number 3 / November 2008, pp. 111-127, DOI: 10.1002/sam.10012, 2008. [ EE (Wiley InterScience) | implementation within the ELKI framework (webpage) ] |
| [22] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Detecting Clusters in Moderate-to-high Dimensional Data: Subspace Clustering, Pattern-based Clustering, Correlation Clustering Tutorial at the 34th International Conference on Very Large Databases (VLDB 2008), Auckland, New Zealand, 2008. [ abstract (pdf) | EE (VLDB endowment) | slides (pdf) ] |
| [21] | Hans-Peter Kriegel, Matthias Schubert, Arthur Zimek:
Angle-Based Outlier Detection in High-dimensional Data Proc. 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008), Las Vegas, NV, 2008. [ EE (ACM) | paper (pdf) ] |
| [20] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Detecting Clusters in Moderate-to-high Dimensional Data: Subspace Clustering, Pattern-based Clustering, Correlation Clustering Tutorial at the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008), Las Vegas, NV, 2008. [ slides (pdf) ] |
| [19] | Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
A General Framework for Increasing the Robustness of PCA-based Correlation Clustering Algorithms Proc. 20th International Conference on Scientific and Statistical Database Management (SSDBM 2008), Hong Kong, China, 2008. [ EE (springerlink) | paper (pdf) ] |
| [18] | Elke Achtert, Hans-Peter Kriegel, Arthur Zimek:
ELKI: A Software System for Evaluation of Subspace Clustering Algorithms Proc. 20th International Conference on Scientific and Statistical Database Management (SSDBM 2008), Hong Kong, China, 2008. [ EE (springerlink) | paper (pdf) | poster (pdf) | ELKI software presentation (webpage) | ELKI software documentation (webpage) ] |
| [17] | Arthur Zimek:
Correlation Clustering PhD thesis, Ludwig-Maximilians-Universität München, Munich, Germany, 2008. [ EE (Universitätsbibliothek) | Runner-Up of the 2009 SIGKDD Doctoral Dissertation Award ] |
| [16] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Detecting Clusters in Moderate-to-high Dimensional Data: Subspace Clustering, Pattern-based Clustering, Correlation Clustering Tutorial at the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2008), Osaka, Japan, 2008. [ abstract | slides (pdf) ] |
| [15] | Elke Achtert, Christian Böhm, Jörn David, Peer Kröger, Arthur Zimek:
Robust Clustering in Arbitrarily Oriented Subspaces Proc. 8th SIAM International Conference on Data Mining (SDM 2008), Atlanta, GA, 2008. [ paper (pdf) | Best Paper Honorable Mention Award | implementation within the ELKI framework (webpage) ] |
| [14] | Johannes Aßfalg, Jing Gong, Hans-Peter Kriegel, Alexey Pryakhin, Tiandi Wei, Arthur Zimek:
Supervised Ensembles of Prediction Methods for Subcellular Localization Proc. 6th Asia Pacific Bioinformatics Conference (APBC 2008), Kyoto, Japan, 2008. [ paper (pdf) | talk (pdf) | prediction server ] |
2007 |
|
| [13] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Detecting Clusters in Moderate-to-high Dimensional Data: Subspace Clustering, Pattern-based Clustering, Correlation Clustering Tutorial at the 7th International Conference on Data Mining (ICDM 2007), Omaha, NE, 2007. [ abstract | slides (pdf) ] |
| [12] | Hans-Peter Kriegel, Karsten M. Borgwardt, Peer Kröger, Alexey Pryakhin, Matthias Schubert, Arthur Zimek:
Future Trends in Data Mining Data Mining and Knowledge Discovery, Volume 15, Number 1 / August 2007, pp. 87-97, DOI: 10.1007/s10618-007-0067-9, 2007. [ EE (springerlink) ] |
| [11] | Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
On Exploring Complex Relationships of Correlation Clusters Proc. 19th International Conference on Scientific and Statistical Database Management (SSDBM 2007), Banff, Canada, 2007. [ paper (pdf) | talk (pdf) | implementation within the ELKI framework (webpage) ] |
| [10] | Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Robust, Complete, and Efficient Correlation Clustering Proc. 7th SIAM International Conference on Data Mining (SDM'07), Minneapolis, MN, 2007. [ paper (pdf) | poster (pdf) | implementation within the ELKI framework (webpage) | EE (SIAM) ] |
| [9] | Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Ina Müller-Gorman, Arthur Zimek:
Detection and Visualization of Subspace Cluster Hierarchies Proc. 12th International Conference on Database Systems for Advanced Applications (DASFAA'07), Bangkok, Thailand, 2007. [ paper (pdf) | implementation within the ELKI framework (webpage) ] |
| [8] | Hans-Peter Kriegel, Stefan Brecheisen, Peer Kröger, Martin Pfeifle, Matthias Schubert, Arthur Zimek:
Density-Based Data Analysis and Similarity Search In Petrushin V. A., Khan L. (eds.): Multimedia Data Mining and Knowledge Discovery, Springer, 2007. [ draft (pdf) ] |
2006 |
|
| [7] | Hans-Peter Kriegel, Alexey Pryakhin, Matthias Schubert, Arthur Zimek:
COSMIC: Conceptually Specified Multi-Instance Clusters Proc. 6th International Conference on Data Mining (ICDM 2006), Hong Kong, China, 2006. [ EE (ieeecomputersociety) ] |
| [6] | Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Ina Müller-Gorman, Arthur Zimek:
Finding Hierarchies of Subspace Clusters Proc. 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'06), Berlin, Germany, 2006. [ paper (pdf) | poster (pdf) ] |
| [5] | Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Deriving Quantitative Models for Correlation Clusters Proc. of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2006), Philadelphia, PA, 2006. [ paper (pdf) | talk (pdf) | implementation within the ELKI framework (webpage) ] |
| [4] | Elke Achtert, Christian Böhm, Peer Kröger, Arthur Zimek:
Mining Hierarchies of Correlation Clusters Proc. 18th International Conference on Scientific and Statistical Database Management (SSDBM 2006), Vienna, Austria, 2006. [ paper (pdf) | talk (pdf) ] |
2005 |
|
| [3] | Arthur Zimek:
Hierarchical Classification Using Ensembles of Nested Dichotomies Diploma Thesis, TU/LMU Munich, 2005. [ complete material | see also ] |
2004 |
|
| [2] | Arthur Zimek, Eibe Frank, Stefan Kramer:
Ensembles of Nested Dichotomies for Hierarchical Classification and Their Application to SCOP Poster at the German Conference on Bioinformatics (GCB-2004), 2004. [ poster (pdf) ] |
| [1] | Christian Böhm, Karin Kailing, Peer Kröger, Arthur Zimek:
Computing Clusters of Correlation Connected Objects Proc. ACM SIGMOD International Conference on Management of Data (SIGMOD'04), Paris, France, pp. 455-467, 2004. [ paper (pdf) | implementation within the ELKI framework (webpage) ] |
External Listing
- google scholar
- ACM author page
- DBLP
- Aminer
-
A great resource for information on current trends in data mining is: www.KDnuggets.com - Analytics, Big Data, Data Mining, and Data Science Resources
KDnuggets listed some of my work, see for example: http://www.kdnuggets.com/2015/09/most-popular-statistical-analysis-data-mining-papers.html.