Arthur Zimek

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Arthur Zimek
Alma materLudwig-Maximilians-Universität München
Scientific career
Fieldsoutlier detection, correlation clustering
InstitutionsUniversity of Southern Denmark, University of Alberta, Ludwig-Maximilians-Universität München
Doctoral advisorHans-Peter Kriegel

Arthur Zimek is a professor in data mining, data science and machine learning at the University of Southern Denmark in Odense, Denmark.

He graduated from the Ludwig Maximilian University of Munich in Munich, Germany, where he worked with Prof. Hans-Peter Kriegel.[1] His dissertation on "Correlation Clustering" was awarded the "SIGKDD Doctoral Dissertation Award 2009 Runner-up"[2] by the Association for Computing Machinery.

He is well known[3] for his work on outlier detection,[4][5] density-based clustering,[6]correlation clustering,[7][8] and the curse of dimensionality.[9][10]

He is one of the founders and core developers of the open-source ELKI data mining framework.[11][12]


  1. ^ News, SIGKDD. "SIGKDD Awards : 2015 SIGKDD Innovation Award: Hans-Peter Kriegel". Retrieved 2017-05-29. with his team members Peer Kroeger, Erich Schubert and Arthur Zimek
  2. ^ "SIGKDD Doctoral Dissertation Award". ACM SIGKDD. Archived from the original on 2010-11-29. Retrieved 30 May 2010.
  3. ^ E.g. Aggarwal, Charu C. (2016-12-10). Outlier analysis. Springer. pp. 49pp. ISBN 9783319475783. OCLC 967215852.
  4. ^ Kriegel, Hans-Peter; Schubert, Matthias; Zimek, Arthur (2008). Angle-based Outlier Detection in High-dimensional Data. Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. KDD '08. New York, NY, USA: ACM. pp. 444–452. CiteSeerX . doi:10.1145/1401890.1401946. ISBN 9781605581934. S2CID 3072058.
  5. ^ Kriegel, Hans-Peter; Kröger, Peer; Schubert, Erich; Zimek, Arthur (2009). LoOP: Local Outlier Probabilities. Proceedings of the 18th ACM Conference on Information and Knowledge Management. CIKM '09. New York, NY, USA: ACM. pp. 1649–1652. doi:10.1145/1645953.1646195. ISBN 9781605585123. S2CID 14401236.
  6. ^ Kriegel, Hans-Peter; Kröger, Peer; Sander, Jörg; Zimek, Arthur (2011-04-05). "Density-based clustering". Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 1 (3): 231–240. doi:10.1002/widm.30. S2CID 36920706.
  7. ^ Böhm, Christian; Kailing, Karin; Kröger, Peer; Zimek, Arthur (2004). Computing Clusters of Correlation Connected Objects. Proceedings of the 2004 ACM SIGMOD International Conference on Management of Data. SIGMOD '04. New York, NY, USA: ACM. pp. 455–466. CiteSeerX . doi:10.1145/1007568.1007620. ISBN 978-1581138597. S2CID 6411037.
  8. ^ Achtert, E.; Böhm, C.; David, J.; Kröger, P.; Zimek, A. (2008-04-24). Proceedings of the 2008 SIAM International Conference on Data Mining. Proceedings. Society for Industrial and Applied Mathematics. pp. 763–774. doi:10.1137/1.9781611972788.69. ISBN 9780898716542.
  9. ^ Zimek, Arthur; Erich, Schubert; Hans-Peter, Kriegel (2012-08-27). "A survey on unsupervised outlier detection in high-dimensional numerical data". Statistical Analysis and Data Mining. 5 (5): 5. doi:10.1002/sam.11161.
  10. ^ Houle, Michael E.; Kriegel, Hans-Peter; Kröger, Peer; Schubert, Erich; Zimek, Arthur (2010-06-30). Can Shared-Neighbor Distances Defeat the Curse of Dimensionality?. Scientific and Statistical Database Management. Lecture Notes in Computer Science. 6187. Springer, Berlin, Heidelberg. pp. 482–500. CiteSeerX . doi:10.1007/978-3-642-13818-8_34. ISBN 978-3-642-13817-1.
  11. ^ Achtert, Elke; Kriegel, Hans-Peter; Zimek, Arthur (2008-07-09). ELKI: A Software System for Evaluation of Subspace Clustering Algorithms. Scientific and Statistical Database Management. Lecture Notes in Computer Science. 5069. Springer, Berlin, Heidelberg. pp. 580–585. CiteSeerX . doi:10.1007/978-3-540-69497-7_41. ISBN 978-3-540-69476-2.
  12. ^ "The ELKI Team". Retrieved 2017-05-29.

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Edited: 2021-06-18 18:09:58