Arthur Zimek

Search results

• 2024

  Evaluating outlier probabilities: assessing sharpness, refinement, and calibration using stratified and weighted measures

  Röchner, P., Marques, H. O., Campello, R. J. G. B. & Zimek, A., 2024, (E-pub ahead of print) In: Data Mining and Knowledge Discovery.

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  • Outlier Detection 100%
  • Detection Algorithm 66%
  • Joints (Structural Components) 33%
  • Domain Expert 33%
• 2023

  Anomaly detection in streaming data: A comparison and evaluation study

  Iglesias Vázquez, F., Hartl, A., Zseby, T. & Zimek, A., Dec 2023, In: Expert Systems with Applications. 233, 20 p., 120994.

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  File

  • Comparison Study 100%
  • Evaluation Study 100%
  • Data Streaming 100%
  • Anomaly Detection 100%
  • Domain Knowledge 25%
  542 Downloads (Pure)

• On the evaluation of outlier detection and one-class classification: a comparative study of algorithms, model selection, and ensembles

  Marques, H. O., Swersky, L., Sander, J., Campello, R. J. G. B. & Zimek, A., 2023, In: Data Mining and Knowledge Discovery. 37, 4, p. 1473-1517

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  File

  • Outlier Detection 100%
  • Class Classification 100%
  • Detection Method 100%
  • Outlier Detection Method 75%
  • Machine Learning 66%
  19 Downloads (Pure)
• 2021

  Clustering refinement

  Iglesias, F., Zseby, T. & Zimek, A., Oct 2021, In: International Journal of Data Science and Analytics. 12, 4, p. 333-353

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  File

  • Cluster Analysis 100%
  • Interpretability 50%
  • Clustering Technique 50%
  • Cluster Validity 50%
  43 Downloads (Pure)

• Outlier detection with explanations on music streaming data: A case study with danmark music group ltd.

  Sejr, J. H., Christiansen, T., Dvinge, N., Hougesen, D., Schneider-Kamp, P. & Zimek, A., 1. Mar 2021, In: Applied Sciences. 11, 5, 14 p., 2270.

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  File

  • Outlier Detection 100%
  • Case Study 100%
  • Data Streaming 100%
  • Model Prediction 100%
  • Neural Network 50%
  64 Downloads (Pure)
• 2020

  Absolute Cluster Validity

  Iglesias Vazquez, F., Zseby, T. & Zimek, A., Sept 2020, In: IEEE Transaction on Pattern Analysis and Machine Intelligence. 42, 9, p. 2096-2112

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Data Structure 100%
  • Computational Effort 100%
  • Solution Space 100%
  • Multimodality 100%
  • Cluster Validity 100%

• Density-based clustering

  Campello, R. J. G. B., Kröger, P., Sander, J. & Zimek, A., Apr 2020, In: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 10, 2, 15 p., e1343.

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  File

  • Contiguous Region 100%
  • Clustering 100%
  • Density-Based Cluster 100%
  • Ensemble Method 50%
  • Data Preprocessing 50%
  3142 Downloads (Pure)

• Internal Evaluation of Unsupervised Outlier Detection

  Marques, H. O., Campello, R. J. G. B., Sander, J. & Zimek, A., 9. Jul 2020, In: ACM Transactions on Knowledge Discovery from Data. 14, 4, 47.

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Outlier Detection 100%
  • Detection Result 37%
  • Cluster Analysis 12%
• 2019

  A unified view of density-based methods for semi-supervised clustering and classification

  Castro Gertrudes, J., Zimek, A., Sander, J. & Campello, R. J. G. B., Nov 2019, In: Data Mining and Knowledge Discovery. 33, 6, p. 1894-1952 59 p.

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  • Clustering Algorithm 100%
  • Supervised Classification 100%
  • Big Data 50%
  • Experimental Result 50%
  • Building-Blocks 50%

• ELKI: A large open-source library for data analysis: ELKI Release 0.7.5 "Heidelberg"

  Schubert, E. & Zimek, A., 10. Feb 2019, In: arxiv.org. 134 p., abs/1902.03616.

  Research output: Contribution to journal › Journal article › Research

  Open Access

  • Data Mining 100%
  • Open-Source Library 100%
  • Outlier Detection 50%
  • Open Source 50%
  • Benchmarking 50%

• Establishing a many-cytokine signature via multivariate anomaly detection

  Dingle, K., Zimek, A., Azizieh, F. & Ansari, A. R., 1. Dec 2019, In: Scientific Reports. 9, 1, 13 p., 9684.

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  File

  • Statistical Method 100%
  • Medical Condition 100%
  • Anomaly Detection 100%
  • Cytokine 100%
  • Detection Algorithm 40%
  51 Downloads (Pure)

• MDCGen: multidimensional dataset generator for clustering

  Iglesias, F., Zseby, T., Ferreira, D. & Zimek, A., 1. Oct 2019, In: Journal of Classification. 36, 3, p. 599-618 20 p.

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  File

  • Customisation 100%
  • Clustering Algorithm 100%
  • Classification Algorithm 100%
  • Benchmarking 100%
  • Synthetic Datasets 100%
  152 Downloads (Pure)

• Outlier detection in graphs: A study on the impact of multiple graph models

  Campos, G. O., Moreira, E., Meira, W. & Zimek, A., 2019, In: Computer Science and Information Systems. 16, 2, p. 565-595 31 p.

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  File

  • Outlier Detection 100%
  • Graph Model 100%
  • Detect Outlier 25%
  • Detecting Outlier 25%
  • Similarities 25%
  85 Downloads (Pure)
• 2018

  There and back again: Outlier detection between statistical reasoning and data mining algorithms

  Zimek, A. & Filzmoser, P., 1. Nov 2018, In: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 8, 6, 26 p., e1280.

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  File

  • Outlier Detection 100%
  • Data Mining Algorithm 100%
  • Data Mining 40%
  • Research Topic 20%
  • Data Mining Technique 20%
  3740 Downloads (Pure)
• 2017

  The (black) art of runtime evaluation: Are we comparing algorithms or implementations?

  Kriegel, H.-P., Schubert, E. & Zimek, A., 2017, In: Knowledge and Information Systems. 52, 2, p. 341–378 38 p.

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Big Data 100%
  • Outlier Detection Method 100%
• 2016

  On strategies for building effective ensembles of relative clustering validity criteria

  Jaskowiak, P. A., Moulavi, D., Furtado, A. C. S., Campello, R. J. G. B., Zimek, A. & Sander, J., 2016, In: Knowledge and Information Systems. 47, 2, p. 329-354

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Criterion Validity 100%
  • Application Scenario 33%
  • Synthetic Datasets 33%
  • Clustering Result 33%
  • Superior Performance 33%

• On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study

  Campos, G. O., Zimek, A., Sander, J., Campello, R. J. G. B., Micenková, B., Schubert, E., Assent, I. & Houle, M. E., 2016, In: Data Mining and Knowledge Discovery. 30, 4, p. 891-927

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Outlier Detection 100%
  • Detection Method 100%
  • Experimental Study 50%
  • Outlier Detection Method 28%
  • Detection Algorithm 14%
• 2015

  A Framework for Clustering Uncertain Data

  Schubert, E., Koos, A., Emrich, T., Züfle, A., Schmid, K. A. & Zimek, A., 2015, In: Proceedings of the VLDB Endowment. 8, 12, p. 1976-1979 4 p.

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Model Uncertainty 100%
  • Research Community 100%
  • Distance Measure 100%
  • Evaluation Measure 100%
  • Indexing Technique 100%

• Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection

  Campello, R. J. G. B., Moulavi, D., Zimek, A. & Sander, J., 2015, In: ACM Transactions on Knowledge Discovery from Data. 10, 1, p. 1-51 5.

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Outlier Detection 100%
  • Clustered Data 100%
  • Density Estimate 100%
  • Density Threshold 100%
  • Scientific Visualization 100%

• Intrinsic dimensional outlier detection in high-dimensional data

  Von Brünken, J., Houle, M. E. & Zimek, A., Mar 2015, In: NII Technical Reports. 2015, 3, p. 1-12

  Research output: Contribution to journal › Journal article › Research

  Open Access

  • Outlier Detection 100%
  • Dimensional Data 100%
  • State of the Art 100%
  • Detection Method 100%
  • Function Similarity 50%

• The blind men and the elephant: on meeting the problem of multiple truths in data from clustering and pattern mining perspectives

  Zimek, A. & Vreeken, J., Jan 2015, In: Machine Learning. 98, 1-2, p. 121-155

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Pattern Mining 100%
  • Clustering 100%
  • Branches 100%
  • Fundamental Problem 66%
  • Common Root 50%
• 2014

  Ensembles for unsupervised outlier detection: challenges and research questions a position paper

  Zimek, A., Campello, R. J. G. B. & Sander, J., 2014, In: S I G K D D Explorations. 15, 1, p. 11-22

  Research output: Contribution to journal › Journal article › Research › peer-review

• Local outlier detection reconsidered: A generalized view on locality with applications to spatial, video, and network outlier detection

  Schubert, E., Zimek, A. & Kriegel, H. P., Jan 2014, In: Data Mining and Knowledge Discovery. 28, 1, p. 190-237

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Local 100%
  • Spatial 100%
  • Locale 100%
  • Outlier Detection 100%
  • Framework 75%
• 2013

  A framework for semi-supervised and unsupervised optimal extraction of clusters from hierarchies

  Campello, R. J. G. B., Moulavi, D., Zimek, A. & Sander, J., Nov 2013, In: Data Mining and Knowledge Discovery. 27, 3, p. 344-371

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Optimization Problem 100%
  • Real Data Sets 100%
  • Globally Optimal Solution 100%
  • Algorithmic Efficiency 100%

• A survey on enhanced subspace clustering

  Sim, K., Gopalkrishnan, V., Zimek, A. & Cong, G., Mar 2013, In: Data Mining and Knowledge Discovery. 26, 2, p. 332-397

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Clustering 100%
  • Clustering Algorithm 100%
  • Clustering Result 50%
• 2012

  A survey on unsupervised outlier detection in high-dimensional numerical data

  Zimek, A., Schubert, E. & Kriegel, H. P., Oct 2012, In: Statistical Analysis and Data Mining. 5, 5, p. 363-387

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Outlier Detection 100%
  • Numerical Data 100%
  • Dimensional Data 75%
  • Irrelevant Attribute 75%
  • Euclidean Space 50%

• Subspace clustering

  Kriegel, H. P., Kröger, P. & Zimek, A., Dec 2012, In: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 2, 4, p. 351-364

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Research Direction 100%
  • Data Record 100%
• 2011

  Density-based clustering

  Kriegel, H. P., Kröger, P., Sander, J. & Zimek, A., May 2011, In: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 1, 3, p. 231-240

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Space Data 100%
  • Density-Based Cluster 100%
• 2010

  A study of hierarchical and flat classification of proteins

  Zimek, A., Buchwald, F., Frank, E. & Kramer, S., 2. Jun 2010, In: IEEE/ACM Transactions on Computational Biology and Bioinformatics. 7, 3, p. 563-571

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Class Hierarchy 100%
  • Decision Trees 66%
  • Classification Performance 66%
  • Experimental Result 33%
  • Logistic Regression 33%

• Investigating a correlation between subcellular localization and fold of proteins

  Aßfalg, J., Gong, J., Kriegel, H. P., Pryakhin, A., Wei, T. & Zimek, A., 21. May 2010, In: Journal of Universal Computer Science. 16, 5, p. 604-621

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  File

  • Subcellular Localization 100%
  • Cellular Distribution 100%
  • Conformation 20%
  • Protein Secondary Structure 20%
  • Protein Classification 20%
  25 Downloads (Pure)
• 2009

  Can shared-neighbor distances defeat the curse of dimensionality?

  Houle, M. E., Kriegel, H. P., Kröger, P., Schubert, E. & Zimek, A., 24. Dec 2009, In: NII Technical Reports. 18, p. 1-29

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Distance Measure 100%
  • Data Distribution 100%
  • Similarity Measure 100%
  • Curse of Dimensionality 100%
  • Data Mining 50%

• Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering

  Kriegel, H. P., Kröger, P. & Zimek, A., Mar 2009, In: ACM Transactions on Knowledge Discovery from Data. 3, 1, 58 p., 1.

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Clustering 100%
  • Proposition 100%
  • Dimensional Data 100%
  • Data Mining 100%
  • High Dimensional Data 100%

• Subspace and projected clustering: Experimental evaluation and analysis

  Moise, G., Zimek, A., Kröger, P., Kriegel, H. P. & Sander, J., Dec 2009, In: Knowledge and Information Systems. 21, 3, p. 299-326

  Research output: Contribution to journal › Journal article › Research › peer-review

  • Clustering Technique 100%
  • High Dimensional Data 50%
• 2008

  Detecting clusters in moderate-to-high dimensional data: Subspace clustering, pattern-based clustering, and correlation clustering

  Kriegel, H. P., Kröger, P. & Zimek, A., Aug 2008, In: Proceedings of the VLDB Endowment. 1, 2, p. 1528-1529

  Research output: Contribution to journal › Journal article › Research › peer-review

  • High Dimensional Data 100%
  • Problem Definition 100%
  • Data Mining 50%
  • Ad Hoc Solution 50%
  • Tacit Assumption 50%

• Global Correlation Clustering Based on the Hough Transform

  Achtert, E., Böhm, C., David, J., Kröger, P. & Zimek, A., Nov 2008, In: Statistical Analysis and Data Mining. 1, 3, p. 111-127

  Research output: Contribution to journal › Journal article › Research › peer-review
• 2007

  Future trends in data mining

  Kriegel, H. P., Borgwardt, K. M., Kröger, P., Pryakhin, A., Schubert, M. & Zimek, A., Aug 2007, In: Data Mining and Knowledge Discovery. 15, 1, p. 87-97

  Research output: Contribution to journal › Journal article › Research › peer-review

  Open Access

  • Data Mining 100%
  • Computer Science 16%