LMU MünchenInstitut für InformatikDr. Arthur ZimekLFE Datenbanksysteme
 
 
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List of Publications

not updated anymore, see my new page: http://www.imada.sdu.dk/~zimek

2016

[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) ]
[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) ]

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