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Research Output 2004 2019

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Journal article
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 journalJournal articleResearchpeer-review

Clustering algorithms
Supervised learning
Acoustic waves
Big data

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 journalJournal articleResearch

Open Access
Data mining
Cluster analysis
Benchmarking
Scalability
Students

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 journalJournal articleResearchpeer-review

Open Access
Pregnancy Complications
Allergy and Immunology
Reference Values
Datasets
21 Downloads (Pure)

MDCGen: multidimensional dataset generator for clustering

Iglesias, F., Zseby, T., Ferreira, D. & Zimek, A., 23. Apr 2019, In : Journal of Classification. 20 p.

Research output: Contribution to journalJournal articleResearchpeer-review

Open Access
File
Testing
Benchmarking
Clustering algorithms
30 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 journalJournal articleResearchpeer-review

Open Access
File
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 journalJournal articleResearchpeer-review

Experiments
Scalability
Big data
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 journalJournal articleResearchpeer-review

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 journalJournal articleResearchpeer-review

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 journalJournal articleResearchpeer-review

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

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

Research output: Contribution to journalJournal articleResearchpeer-review

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 journalJournal articleResearch

Open Access
Outlier Detection
High-dimensional Data
Outlier
Continuous random variable
Density Estimation

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 journalJournal articleResearchpeer-review

2014

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 journalJournal articleResearchpeer-review

Experiments
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 journalJournal articleResearchpeer-review

Experiments

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

Zimek, A., Campello, R. J. G. B. & Sander, J., Jun 2013, In : S I G K D D Explorations. 15, 1, p. 11-22

Research output: Contribution to journalJournal articleResearchpeer-review

2012

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 journalJournal articleResearchpeer-review

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 journalJournal articleResearchpeer-review

Proteins
Protein
Multi-class
Decision Trees
Decision tree
1 Downloads (Pure)

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 journalJournal articleResearchpeer-review

Open Access
File
Fold
Proteins
Protein
Secondary Structure
Feature Vector
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 journalJournal articleResearchpeer-review

Data mining

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 journalJournal articleResearchpeer-review

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 journalJournal articleResearchpeer-review

Data mining

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 journalJournal articleResearchpeer-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 journalJournal articleResearchpeer-review

Open Access
Data mining
Computer science