World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
14966
World Ranking
6322
National Ranking
20

Overview

Arthur Zimek is affiliated with the University of Southern Denmark in Denmark. Their primary field of study is Computer Science, with a significant focus on Artificial Intelligence, where they have contributed to 65 publications. Additional subfields in their research include Computer Vision and Pattern Recognition, Signal Processing, Computer Networks and Communications, and Epidemiology.

Their research topics encompass several areas related to data analysis and machine learning. Key topics include:

  • Anomaly Detection Techniques and Applications
  • Machine Learning and Data Classification
  • Privacy-Preserving Technologies in Data
  • Data-Driven Disease Surveillance
  • Data Management and Algorithms
  • Water Systems and Optimization
  • Data Quality and Management

Arthur Zimek has published frequently in venues such as:

  • arXiv (Cornell University)
  • Data Mining and Knowledge Discovery
  • Big Data
  • Expert Systems with Applications
  • Proceedings of the 31st ACM International Conference on Information & Knowledge Management

The scientist has multiple recent publications highlighting their research focus. Notable papers include:

  • Internal Evaluation of Unsupervised Outlier Detection, 2020, ACM Transactions on Knowledge Discovery from Data
  • Anomaly detection in streaming data: A comparison and evaluation study, 2023, Expert Systems with Applications
  • On the evaluation of outlier detection and one-class classification: a comparative study of algorithms, model selection, and ensembles, 2023, Data Mining and Knowledge Discovery
  • Syntheval: a framework for detailed utility and privacy evaluation of tabular synthetic data, 2024, Data Mining and Knowledge Discovery
  • A Simple Meta-path-free Framework for Heterogeneous Network Embedding, 2022, Proceedings of the 31st ACM International Conference on Information & Knowledge Management

Collaborations play a role in Arthur Zimek's work, with frequent co-authors including Anton D. Lautrup, Peter Schneider-Kamp, Ricardo J. G. B. Campello, Tobias Hyrup, and Eirini Ntoutsi.

Arthur Zimek has also contributed to book publications under the Springer Science+Business Media label. These include:

  • ECML PKDD 2020 Workshops, 2020
  • Similarity Search and Applications, 2020

Best Publications

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

    Hans-Peter Kriegel;Peer Kröger;Arthur Zimek

  • Density-based clustering

    Hans Peter Kriegel;Peer Kröger;Jörg Sander;Arthur Zimek

  • Angle-based outlier detection in high-dimensional data

    Hans-Peter Kriegel;Matthias Schubert;Arthur Zimek

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

    Arthur Zimek;Erich Schubert;Hans-Peter Kriegel

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

    Ricardo J. G. B. Campello;Davoud Moulavi;Arthur Zimek;Jörg Sander

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

    Guilherme O. Campos;Arthur Zimek;Jörg Sander;Ricardo J. Campello

  • LoOP: local outlier probabilities

    Hans-Peter Kriegel;Peer Kröger;Erich Schubert;Arthur Zimek

  • Density‐based clustering

    Unknown

  • Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data

    Hans-Peter Kriegel;Peer Kröger;Erich Schubert;Arthur Zimek

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

    Erich Schubert;Arthur Zimek;Hans-Peter Kriegel

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

    Arthur Zimek;Ricardo J.G.B. Campello;Jörg Sander

  • Can shared-neighbor distances defeat the curse of dimensionality?

    Michael E. Houle;Hans-Peter Kriegel;Peer Kröger;Erich Schubert

  • Interpreting and Unifying Outlier Scores

    Hans-Peter Kriegel;Peer Kröger;Erich Schubert;Arthur Zimek

  • Density-based clustering validation

    Davoud Moulavi;Pablo A. Jaskowiak;Pablo A. Jaskowiak;Ricardo J.G.B. Campello;Arthur Zimek

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

    Hans-Peter Kriegel;Erich Schubert;Arthur Zimek

  • Future trends in data mining

    Hans-Peter Kriegel;Karsten M. Borgwardt;Peer Kröger;Alexey Pryakhin

  • Subsampling for efficient and effective unsupervised outlier detection ensembles

    Arthur Zimek;Matthew Gaudet;Ricardo J.G.B. Campello;Jörg Sander

  • Computing Clusters of Correlation Connected objects

    Christian Böhm;Karin Kailing;Peer Kröger;Arthur Zimek

  • A framework for clustering uncertain data

    Erich Schubert;Alexander Koos;Tobias Emrich;Andreas Züfle

  • On Evaluation of Outlier Rankings and Outlier Scores

    Erich Schubert;Remigius Wojdanowski;Arthur Zimek;Hans Peter Kriegel

  • Subspace clustering

    Hans-Peter Kriegel;Peer Kröger;Arthur Zimek

Frequent Co-Authors

Hans-Peter Kriegel
Hans-Peter Kriegel Ludwig-Maximilians-Universität München
Peer Kröger
Peer Kröger Kiel University
Ricardo J. G. B. Campello
Ricardo J. G. B. Campello University of Southern Denmark
Jörg Sander
Jörg Sander University of Alberta
Ira Assent
Ira Assent Aarhus University
Jilles Vreeken
Jilles Vreeken Max Planck Society
Wagner Meira
Wagner Meira Universidade Federal de Minas Gerais
Thomas Seidl
Thomas Seidl Ludwig-Maximilians-Universität München
Carlotta Domeniconi
Carlotta Domeniconi George Mason University
Youcef Djenouri
Youcef Djenouri University of South-Eastern Norway

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