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ORCIDArthur Zimek
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- affiliation: University of Southern Denmark, Odense, Denmark
- affiliation: Ludwig Maximilian University of Munich, Germany
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2020 – today
- 2025
[j41]Anton Danholt Lautrup, Tobias Hyrup, Arthur Zimek, Peter Schneider-Kamp:
Syntheval: a framework for detailed utility and privacy evaluation of tabular synthetic data. Data Min. Knowl. Discov. 39(1): 1-25 (2025)- [j40]Félix Iglesias Vázquez, Henrique O. Marques, Arthur Zimek, Tanja Zseby:
What do anomaly scores actually mean? Dynamic characteristics beyond accuracy. Data Min. Knowl. Discov. 39(1): 1-59 (2025) - 2024
- [j39]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 Min. Knowl. Discov. 38(6): 3719-3757 (2024) - [c79]Yi Cai, Arthur Zimek, Eirini Ntoutsi, Gerhard Wunder:
Transparent Neighborhood Approximation for Text Classifier Explanation by Probability-Based Editing. DSAA 2024: 1-10 - [c78]Alastair Anderberg, James Bailey, Ricardo J. G. B. Campello, Michael E. Houle, Henrique O. Marques
, Milos Radovanovic, Arthur Zimek:
Dimensionality-Aware Outlier Detection. SDM 2024: 652-660 - [c77]Muhammad Rajabinasab, Anton Danholt Lautrup, Tobias Hyrup, Arthur Zimek:
A Dynamic Evaluation Metric for Feature Selection. SISAP 2024: 65-72 - [c76]Camilla Birch Okkels, Martin Aumüller, Arthur Zimek:
On the Design of Scalable Outlier Detection Methods Using Approximate Nearest Neighbor Graphs. SISAP 2024: 170-184 - [c75]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. SISAP 2024: 215-222 - [i13]Alastair Anderberg, James Bailey, Ricardo J. G. B. Campello, Michael E. Houle, Henrique O. Marques, Milos Radovanovic, Arthur Zimek:
Dimensionality-Aware Outlier Detection: Theoretical and Experimental Analysis. CoRR abs/2401.05453 (2024) - [i12]Anton Danholt Lautrup, Tobias Hyrup, Arthur Zimek, Peter Schneider-Kamp:
SynthEval: A Framework for Detailed Utility and Privacy Evaluation of Tabular Synthetic Data. CoRR abs/2404.15821 (2024) - [i11]Muhammad Rajabinasab, Anton Danholt Lautrup, Tobias Hyrup, Arthur Zimek:
FSDEM: Feature Selection Dynamic Evaluation Metric. CoRR abs/2408.14234 (2024) - [i10]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 (Extended Version). CoRR abs/2408.15874 (2024) - 2023
- [j38]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 Min. Knowl. Discov. 37(4): 1473-1517 (2023) - [j37]Félix Iglesias Vázquez, Alexander Hartl, Tanja Zseby, Arthur Zimek:
Anomaly detection in streaming data: A comparison and evaluation study. Expert Syst. Appl. 233: 120994 (2023) - [c74]Jonatan Møller Nuutinen Gøttcke, Colin Bellinger, Paula Branco, Arthur Zimek:
An Interpretable Measure of Dataset Complexity for Imbalanced Classification Problems. SDM 2023: 253-261 - [c73]Félix Iglesias, Tanja Zseby, Alexander Hartl, Arthur Zimek:
SDOclust: Clustering with Sparse Data Observers. SISAP 2023: 185-199 - [i9]Yi Cai, Arthur Zimek, Eirini Ntoutsi, Gerhard Wunder:
Explaining text classifiers through progressive neighborhood approximation with realistic samples. CoRR abs/2302.07733 (2023) - [i8]Tobias Hyrup, Anton Danholt Lautrup, Arthur Zimek, Peter Schneider-Kamp:
Sharing is CAIRing: Characterizing Principles and Assessing Properties of Universal Privacy Evaluation for Synthetic Tabular Data. CoRR abs/2312.12216 (2023) - 2022
- [c72]Rui Zhang, Arthur Zimek, Peter Schneider-Kamp:
A Simple Meta-path-free Framework for Heterogeneous Network Embedding. CIKM 2022: 2600-2609 - [c71]Rui Zhang, Arthur Zimek, Peter Schneider-Kamp:
Unsupervised Representation Learning on Attributed Multiplex Network. CIKM 2022: 2610-2619 - [c70]Yi Cai, Arthur Zimek, Gerhard Wunder, Eirini Ntoutsi:
Power of Explanations: Towards automatic debiasing in hate speech detection. DSAA 2022: 1-10 - [c69]Erik Andersen, Marco Chiarandini, Marwan Hassani, Stefan Jänicke, Panagiotis Tampakis, Arthur Zimek:
Evaluation of Probability Distribution Distance Metrics in Traffic Flow Outlier Detection. MDM 2022: 64-69 - [c68]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 - [c67]Henrique O. Marques, Arthur Zimek, Ricardo J. G. B. Campello, Jörg Sander:
Similarity-Based Unsupervised Evaluation of Outlier Detection. SISAP 2022: 234-248 - [i7]Yi Cai, Arthur Zimek, Gerhard Wunder, Eirini Ntoutsi:
Power of Explanations: Towards automatic debiasing in hate speech detection. CoRR abs/2209.09975 (2022) - 2021
- [j36]Félix Iglesias, Tanja Zseby, Arthur Zimek:
Clustering refinement. Int. J. Data Sci. Anal. 12(4): 333-353 (2021) - [c66]Yi Cai, Arthur Zimek, Eirini Ntoutsi:
XPROAX-Local explanations for text classification with progressive neighborhood approximation. DSAA 2021: 1-10 - [c65]Nicklas Sindlev Andersen, Marco Chiarandini, Stefan Jänicke, Panagiotis Tampakis, Arthur Zimek:
Detecting Wandering Behavior of People with Dementia. ICDM (Workshops) 2021: 727-733 - [c64]Jonatan Møller Nuutinen Gøttcke, Arthur Zimek, Ricardo J. G. B. Campello:
Non-parametric Semi-supervised Learning by Bayesian Label Distribution Propagation. SISAP 2021: 118-132 - [c63]Jonatan Møller Nuutinen Gøttcke, Arthur Zimek:
Handling Class Imbalance in k-Nearest Neighbor Classification by Balancing Prior Probabilities. SISAP 2021: 247-261 - [i6]Yi Cai, Arthur Zimek, Eirini Ntoutsi:
XPROAX-Local explanations for text classification with progressive neighborhood approximation. CoRR abs/2109.15004 (2021) - [i5]Nicklas Sindlev Andersen, Marco Chiarandini, Stefan Jänicke, Panagiotis Tampakis, Arthur Zimek:
Detecting Wandering Behavior of People with Dementia. CoRR abs/2110.13128 (2021) - 2020
- [j35]Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Albrecht Zimmermann:
Call for Special Issue Papers: Evaluation and Experimental Design in Data Mining and Machine Learning. Big Data 8(4): 253-254 (2020) - [j34]Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Albrecht Zimmermann:
Call for Special Issue Papers: Evaluation and Experimental Design in Data Mining and Machine Learning. Big Data 8(5): 456-457 (2020) - [j33]Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Albrecht Zimmermann:
Call for Special Issue Papers: Evaluation and Experimental Design in Data Mining and Machine Learning. Big Data 8(6): 546-547 (2020) - [j32]Jadson Castro Gertrudes, Arthur Zimek, Jörg Sander, Ricardo J. G. B. Campello:
Correction to: A unified view of density-based methods for semi-supervised clustering and classification. Data Min. Knowl. Discov. 34(6): 1984-1985 (2020) - [j31]Félix Iglesias, Tanja Zseby, Arthur Zimek:
Absolute Cluster Validity. IEEE Trans. Pattern Anal. Mach. Intell. 42(9): 2096-2112 (2020) - [j30]Henrique O. Marques, Ricardo J. G. B. Campello, Jörg Sander, Arthur Zimek:
Internal Evaluation of Unsupervised Outlier Detection. ACM Trans. Knowl. Discov. Data 14(4): 47:1-47:42 (2020) - [j29]Ricardo J. G. B. Campello, Peer Kröger, Jörg Sander, Arthur Zimek:
Density-based clustering. WIREs Data Mining Knowl. Discov. 10(2) (2020) - [c62]Félix Iglesias Vázquez, Tanja Zseby, Arthur Zimek:
Interpretability and Refinement of Clustering. DSAA 2020: 21-29 - [c61]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. DSAA 2020: 516-525 - [c60]Rui Zhang, Peter Schneider-Kamp, Arthur Zimek:
Improving Semantic Similarity of Words by Retrofitting Word Vectors in Sense Level. ICAART (2) 2020: 108-119 - [c59]Jonas Herskind Sejr, Arthur Zimek, Peter Schneider-Kamp:
Explainable Detection of Zero Day Web Attacks. ICDIS 2020: 71-78 - [e5]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:
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, Proceedings. Communications in Computer and Information Science 1323, Springer 2020, ISBN 978-3-030-65964-6 [contents] - [e4]Shin'ichi Satoh, Lucia Vadicamo, Arthur Zimek, Fabio Carrara, Ilaria Bartolini, Martin Aumüller, Björn Þór Jónsson, Rasmus Pagh:
Similarity Search and Applications - 13th International Conference, SISAP 2020, Copenhagen, Denmark, September 30 - October 2, 2020, Proceedings. Lecture Notes in Computer Science 12440, Springer 2020, ISBN 978-3-030-60935-1 [contents]
2010 – 2019
- 2019
- [j28]Félix Iglesias, Tanja Zseby, Daniel C. Ferreira, Arthur Zimek:
MDCGen: Multidimensional Dataset Generator for Clustering. J. Classif. 36(3): 599-618 (2019) - [j27]Guilherme Oliveira 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) - [j26]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 Min. Knowl. Discov. 33(6): 1894-1952 (2019) - [c58]Félix Iglesias, 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 - [c57]Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Albrecht Zimmermann:
1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2019). EDML@SDM 2019: 1-3 - [c56]Ruben Becker, Imane Hafnaoui, Michael E. Houle, Pan Li, Arthur Zimek:
Subspace Determination Through Local Intrinsic Dimensional Decomposition. SISAP 2019: 281-289 - [e3]Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Albrecht Zimmermann:
Proceedings of the 1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning co-located with SIAM International Conference on Data Mining (SDM 2019), Calgary, Alberta, Canada, May 4th, 2019. CEUR Workshop Proceedings 2436, CEUR-WS.org 2019 [contents] - [i4]Erich Schubert, Arthur Zimek:
ELKI: A large open-source library for data analysis - ELKI Release 0.7.5 "Heidelberg". CoRR abs/1902.03616 (2019) - [i3]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) - 2018
- [j25]Arthur Zimek, Peter Filzmoser:
There and back again: Outlier detection between statistical reasoning and data mining algorithms. WIREs Data Mining Knowl. Discov. 8(6) (2018) - [c55]Youcef Djenouri, Arthur Zimek, Marco Chiarandini:
Outlier Detection in Urban Traffic Flow Distributions. ICDM 2018: 935-940 - [c54]Félix Iglesias Vázquez, Tanja Zseby, Arthur Zimek:
Outlier Detection Based on Low Density Models. ICDM Workshops 2018: 970-979 - [c53]Guilherme Oliveira Campos, Arthur Zimek, Wagner Meira Jr.:
An Unsupervised Boosting Strategy for Outlier Detection Ensembles. PAKDD (1) 2018: 564-576 - [c52]Michael E. Houle, Erich Schubert, Arthur Zimek:
On the Correlation Between Local Intrinsic Dimensionality and Outlierness. SISAP 2018: 177-191 - [c51]Jadson Castro Gertrudes, Arthur Zimek, Jörg Sander, Ricardo J. G. B. Campello:
A unified framework of density-based clustering for semi-supervised classification. SSDBM 2018: 11:1-11:12 - [c50]Youcef Djenouri, Arthur Zimek:
Outlier Detection in Urban Traffic Data. WIMS 2018: 3:1-3:12 - [c49]Guilherme Oliveira Campos, Wagner Meira Jr., Arthur Zimek:
Outlier Detection in Graphs: On the Impact of Multiple Graph Models. WIMS 2018: 21:1-21:12 - [r3]Peer Kröger, Arthur Zimek:
Subspace Clustering Techniques. Encyclopedia of Database Systems (2nd ed.) 2018 - [r2]Arthur Zimek, Erich Schubert:
Outlier Detection. Encyclopedia of Database Systems (2nd ed.) 2018 - 2017
- [j24]Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
The (black) art of runtime evaluation: Are we comparing algorithms or implementations? Knowl. Inf. Syst. 52(2): 341-378 (2017) - [j23]Guillaume Casanova, Elias Englmeier, Michael E. Houle, Peer Kröger, Michael Nett, Erich Schubert, Arthur Zimek:
Dimensional Testing for Reverse k-Nearest Neighbor Search. Proc. VLDB Endow. 10(7): 769-780 (2017) - [c48]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. SDM 2017: 390-398 - [c47]Evelyn Kirner, Erich Schubert, Arthur Zimek:
Good and Bad Neighborhood Approximations for Outlier Detection Ensembles. SISAP 2017: 173-187 - 2016
- [j22]Guilherme Oliveira 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 Min. Knowl. Discov. 30(4): 891-927 (2016) - [j21]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. Knowl. Inf. Syst. 47(2): 329-354 (2016) - [j20]Ira Assent, Carlotta Domeniconi, Francesco Gullo, Andrea Tagarelli, Arthur Zimek:
MultiClust 2013: Multiple Clusterings, Multiview Data, and Multisource Knowledgedriven Clustering: [Workshop Report]. SIGKDD Explor. 18(1): 35-38 (2016) - [c46]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. DSAA 2016: 1-10 - 2015
- [j19]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. Mach. Learn. 98(1-2): 121-155 (2015) - [j18]Erich Schubert, Alexander Koos, Tobias Emrich, Andreas Züfle, Klaus Arthur Schmid, Arthur Zimek:
A Framework for Clustering Uncertain Data. Proc. VLDB Endow. 8(12): 1976-1979 (2015) - [j17]Ricardo J. G. B. Campello, Davoud Moulavi, Arthur Zimek, Jörg Sander:
Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection. ACM Trans. Knowl. Discov. Data 10(1): 5:1-5:51 (2015) - [c45]Erich Schubert, Arthur Zimek, Hans-Peter Kriegel:
Fast and Scalable Outlier Detection with Approximate Nearest Neighbor Ensembles. DASFAA (2) 2015: 19-36 - [c44]Erich Schubert, Michael Weiler, Arthur Zimek:
Outlier Detection and Trend Detection: Two Sides of the Same Coin. ICDM Workshops 2015: 40-46 - [c43]Henrique O. Marques, Ricardo J. G. B. Campello, Arthur Zimek, Jörg Sander:
On the internal evaluation of unsupervised outlier detection. SSDBM 2015: 7:1-7:12 - [i2]Laurent Amsaleg, Michael E. Houle, Vincent Oria, Arthur Zimek:
Dimensionality and Scalability II: Hands-On Intrinsic Dimensionality (NII Shonan Meeting 2015-9). NII Shonan Meet. Rep. 2015 (2015) - 2014
- [j16]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 Min. Knowl. Discov. 28(1): 190-237 (2014) - [c42]Jundong Li, Jörg Sander, Ricardo J. G. B. Campello, Arthur Zimek:
Active Learning Strategies for Semi-Supervised DBSCAN. Canadian AI 2014: 179-190 - [c41]Mojgan Pourrajabi, Davoud Moulavi, Ricardo J. G. B. Campello, Arthur Zimek, Jörg Sander, Randy Goebel:
Model Selection for Semi-Supervised Clustering. EDBT 2014: 331-342 - [c40]Xuan-Hong Dang, Ira Assent, Raymond T. Ng, Arthur Zimek, Erich Schubert:
Discriminative features for identifying and interpreting outliers. ICDE 2014: 88-99 - [c39]Andreas Züfle, Tobias Emrich, Klaus Arthur Schmid, Nikos Mamoulis, Arthur Zimek, Matthias Renz:
Representative clustering of uncertain data. KDD 2014: 243-252 - [c38]Erich Schubert, Arthur Zimek, Hans-Peter Kriegel:
Generalized Outlier Detection with Flexible Kernel Density Estimates. SDM 2014: 542-550 - [c37]Davoud Moulavi, Pablo A. Jaskowiak, Ricardo J. G. B. Campello, Arthur Zimek, Jörg Sander:
Density-Based Clustering Validation. SDM 2014: 839-847 - [c36]Arthur Zimek, Ricardo J. G. B. Campello, Jörg Sander:
Data perturbation for outlier detection ensembles. SSDBM 2014: 13:1-13:12 - [p2]Arthur Zimek, Ira Assent, Jilles Vreeken:
Frequent Pattern Mining Algorithms for Data Clustering. Frequent Pattern Mining 2014: 403-423 - 2013
- [j15]Kelvin Sim, Vivekanand Gopalkrishnan, Arthur Zimek, Gao Cong:
A survey on enhanced subspace clustering. Data Min. Knowl. Discov. 26(2): 332-397 (2013) - [j14]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 Min. Knowl. Discov. 27(3): 344-371 (2013) - [j13]Arthur Zimek, Ricardo J. G. B. Campello, Jörg Sander:
Ensembles for unsupervised outlier detection: challenges and research questions a position paper. SIGKDD Explor. 15(1): 11-22 (2013) - [c35]Arthur Zimek, Matthew Gaudet, Ricardo J. G. B. Campello, Jörg Sander:
Subsampling for efficient and effective unsupervised outlier detection ensembles. KDD 2013: 428-436 - [c34]Elke Achtert, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
Interactive data mining with 3D-parallel-coordinate-trees. SIGMOD Conference 2013: 1009-1012 - [c33]Erich Schubert, Arthur Zimek, Hans-Peter Kriegel:
Geodetic Distance Queries on R-Trees for Indexing Geographic Data. SSTD 2013: 146-164 - [p1]Arthur Zimek:
Clustering High-Dimensional Data. Data Clustering: Algorithms and Applications 2013: 201-230 - [e2]Ira Assent, Carlotta Domeniconi, Francesco Gullo, Andrea Tagarelli, Arthur Zimek:
Proceedings of the 4th MultiClust Workshop on Multiple Clusterings, Multi-view Data, and Multi-source Knowledge-driven Clustering, in conjunction with KDD 2013, Chicago, IL, USA, August 11, 2013. ACM 2013, ISBN 978-1-4503-2334-5 [contents] - [i1]Michael E. Houle, Vincent Oria, Arthur Zimek:
Dimensionality and Scalability (NII Shonan Meeting 2013-4). NII Shonan Meet. Rep. 2013 (2013) - 2012
- [j12]Arthur Zimek, Erich Schubert, Hans-Peter Kriegel:
A survey on unsupervised outlier detection in high-dimensional numerical data. Stat. Anal. Data Min. 5(5): 363-387 (2012) - [j11]Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Subspace clustering. WIREs Data Mining Knowl. Discov. 2(4): 351-364 (2012) - [c32]Elke Achtert, Sascha Goldhofer, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
Evaluation of Clusterings - Metrics and Visual Support. ICDE 2012: 1285-1288 - [c31]Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
Outlier Detection in Arbitrarily Oriented Subspaces. ICDM 2012: 379-388 - [c30]Irene Ntoutsi, Arthur Zimek, Themis Palpanas, Peer Kröger, Hans-Peter Kriegel:
Density-based Projected Clustering over High Dimensional Data Streams. SDM 2012: 987-998 - [c29]Erich Schubert, Remigius Wojdanowski, Arthur Zimek, Hans-Peter Kriegel:
On Evaluation of Outlier Rankings and Outlier Scores. SDM 2012: 1047-1058 - [e1]Emmanuel Müller, Thomas Seidl, Suresh Venkatasubramanian, Arthur Zimek:
3rd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings, MultiClust '12, in conjunction with SDM 2012, Anaheim, CA, USA, April 28, 2012, Anaheim, CA, USA, April 28, 2012. SIAM 2012 [contents] - 2011
- [j10]Hans-Peter Kriegel, Peer Kröger, Jörg Sander, Arthur Zimek:
Density-based clustering. WIREs Data Mining Knowl. Discov. 1(3): 231-240 (2011) - [c28]Jilles Vreeken, Arthur Zimek:
When Pattern Met Subspace Cluster. MultiClust@ECML/PKDD 2011: 7-18 - [c27]Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
Evaluation of Multiple Clustering Solutions. MultiClust@ECML/PKDD 2011: 55-66 - [c26]Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
Interpreting and Unifying Outlier Scores. SDM 2011: 13-24 - [c25]Thomas Bernecker, Michael E. Houle, Hans-Peter Kriegel, Peer Kröger, Matthias Renz, Erich Schubert, Arthur Zimek:
Quality of Similarity Rankings in Time Series. SSTD 2011: 422-440 - [c24]Elke Achtert, Ahmed Hettab, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
Spatial Outlier Detection: Data, Algorithms, Visualizations. SSTD 2011: 512-516 - [c23]Hans-Peter Kriegel, Peer Kröger, Irene Ntoutsi, Arthur Zimek:
Density Based Subspace Clustering over Dynamic Data. SSDBM 2011: 387-404 - 2010
- [j9]Johannes Aßfalg, Jing Gong, Hans-Peter Kriegel, Alexey Pryakhin, Tiandi Wei, Arthur Zimek:
Investigating a Correlation between Subcellular Localization and Fold of Proteins. J. Univers. Comput. Sci. 16(5): 604-621 (2010) - [j8]Arthur Zimek, Fabian Buchwald, Eibe Frank, Stefan Kramer:
A Study of Hierarchical and Flat Classification of Proteins. IEEE ACM Trans. Comput. Biol. Bioinform. 7(3): 563-571 (2010) - [c22]Elke Achtert, Hans-Peter Kriegel, Lisa Reichert, Erich Schubert, Remigius Wojdanowski, Arthur Zimek:
Visual Evaluation of Outlier Detection Models. DASFAA (2) 2010: 396-399 - [c21]Kyoji Kawagoe, Thomas Bernecker, Hans-Peter Kriegel, Matthias Renz, Arthur Zimek, Andreas Züfle:
Similarity Search in Time Series of Dynamical Model-based Systems. DEXA Workshops 2010: 110-114 - [c20]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. ICDE Workshops 2010: 4-9 - [c19]Hans-Peter Kriegel, Peer Kröger, Irene Ntoutsi, Arthur Zimek:
Towards subspace clustering on dynamic data: an incremental version of PreDeCon. StreamKDD@KDD 2010: 31-38 - [c18]Michael E. Houle, Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
Can Shared-Neighbor Distances Defeat the Curse of Dimensionality? SSDBM 2010: 482-500 - [c17]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. SSDBM 2010: 555-564
2000 – 2009
- 2009
- [j7]Johannes Aßfalg, Jing Gong, Hans-Peter Kriegel, Alexey Pryakhin, Tiandi Wei, Arthur Zimek:
Supervised Ensembles of Prediction Methods for Subcellular Localization. J. Bioinform. Comput. Biol. 7(2): 269-285 (2009) - [j6]Gabriela Moise, Arthur Zimek, Peer Kröger, Hans-Peter Kriegel, Jörg Sander:
Subspace and projected clustering: experimental evaluation and analysis. Knowl. Inf. Syst. 21(3): 299-326 (2009) - [j5]Arthur Zimek:
Correlation clustering. SIGKDD Explor. 11(1): 53-54 (2009) - [j4]Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering. ACM Trans. Knowl. Discov. Data 3(1): 1:1-1:58 (2009) - [c16]Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
LoOP: local outlier probabilities. CIKM 2009: 1649-1652 - [c15]Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data. PAKDD 2009: 831-838 - [c14]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. SSTD 2009: 436-440 - [r1]Peer Kröger, Arthur Zimek:
Subspace Clustering Techniques. Encyclopedia of Database Systems 2009: 2873-2875 - 2008
- [j3]Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Detecting clusters in moderate-to-high dimensional data: subspace clustering, pattern-based clustering, and correlation clustering. Proc. VLDB Endow. 1(2): 1528-1529 (2008) - [j2]Elke Achtert, Christian Böhm, Jörn David, Peer Kröger, Arthur Zimek:
Global Correlation Clustering Based on the Hough Transform. Stat. Anal. Data Min. 1(3): 111-127 (2008) - [c13]Johannes Aßfalg, Jing Gong, Hans-Peter Kriegel, Alexey Pryakhin, Tiandi Wei, Arthur Zimek:
Supervised Ensembles of Prediction Methods for Subcellular Localization. APBC 2008: 29-38 - [c12]Hans-Peter Kriegel, Matthias Schubert, Arthur Zimek:
Angle-based outlier detection in high-dimensional data. KDD 2008: 444-452 - [c11]Elke Achtert, Christian Böhm, Jörn David, Peer Kröger, Arthur Zimek:
Robust Clustering in Arbitrarily Oriented Subspaces. SDM 2008: 763-774 - [c10]Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek:
A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms. SSDBM 2008: 418-435 - [c9]Elke Achtert, Hans-Peter Kriegel, Arthur Zimek:
ELKI: A Software System for Evaluation of Subspace Clustering Algorithms. SSDBM 2008: 580-585 - 2007
- [j1]Hans-Peter Kriegel, Karsten M. Borgwardt, Peer Kröger, Alexey Pryakhin, Matthias Schubert, Arthur Zimek:
Future trends in data mining. Data Min. Knowl. Discov. 15(1): 87-97 (2007) - [c8]Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Ina Müller-Gorman, Arthur Zimek:
Detection and Visualization of Subspace Cluster Hierarchies. DASFAA 2007: 152-163 - [c7]Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Robust, Complete, and Efficient Correlation Clustering. SDM 2007: 413-418 - [c6]Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
On Exploring Complex Relationships of Correlation Clusters. SSDBM 2007: 7 - 2006
- [c5]Hans-Peter Kriegel, Alexey Pryakhin, Matthias Schubert, Arthur Zimek:
COSMIC: Conceptually Specified Multi-Instance Clusters. ICDM 2006: 917-921 - [c4]Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Deriving quantitative models for correlation clusters. KDD 2006: 4-13 - [c3]Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Ina Müller-Gorman, Arthur Zimek:
Finding Hierarchies of Subspace Clusters. PKDD 2006: 446-453 - [c2]Elke Achtert, Christian Böhm, Peer Kröger, Arthur Zimek:
Mining Hierarchies of Correlation Clusters. SSDBM 2006: 119-128 - 2004
- [c1]Christian Böhm, Karin Kailing, Peer Kröger, Arthur Zimek:
Computing Clusters of Correlation Connected Objects. SIGMOD Conference 2004: 455-466
Coauthor Index
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