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Jörg Sander

Active 1996–2026

116
Papers
52,873
Citations
47
h-index
77
i10-index

Citations

Citations per year for Jörg Sander1884: 1 citations1965: 2 citations1981: 1 citations1987: 2 citations1989: 1 citations1990: 1 citations1996: 1 citations1997: 15 citations1998: 41 citations1999: 84 citations2000: 107 citations2001: 151 citations2002: 185 citations2003: 245 citations2004: 286 citations2005: 357 citations2006: 408 citations2007: 434 citations2008: 501 citations2009: 590 citations2010: 604 citations2011: 635 citations2012: 773 citations2013: 862 citations2014: 1,043 citations2015: 1,158 citations2016: 1,445 citations2017: 1,514 citations2018: 1,864 citations2019: 2,319 citations2020: 2,531 citations2021: 2,751 citations2022: 1,746 citations2023: 1,706 citations2024: 1,725 citations2025: 1,227 citations2026: 266 citations2027: 4 citations1885–1964: no citations, so these years are not shown1966–1980: no citations, so these years are not shown1982–1986: no citations, so these years are not shown1988: no citations, so this year is not shown1991–1995: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorChina: 5,233 citing papers, 18.8% of this breakdownUnited States: 4,917 citing papers, 17.6% of this breakdownGermany: 1,921 citing papers, 6.9% of this breakdownUnited Kingdom: 1,140 citing papers, 4.1% of this breakdownCanada: 1,043 citing papers, 3.7% of this breakdownAustralia: 1,021 citing papers, 3.7% of this breakdownItaly: 1,011 citing papers, 3.6% of this breakdownFrance: 955 citing papers, 3.4% of this breakdownIndia: 844 citing papers, 3% of this breakdownJapan: 623 citing papers, 2.2% of this breakdownSouth Korea: 620 citing papers, 2.2% of this breakdownSpain: 543 citing papers, 2% of this breakdown
0%18.8%Other 28.8%

Institutions

Fields

  • Computer Science65%
  • Engineering11%
  • Social Sciences4.7%
  • Biochemistry, Genetics and Molecular Biology4.6%
  • Physics and Astronomy3.1%
  • Medicine2.4%
  • Other9.2%

Topics

  • Anomaly Detection Techniques and Applications6.9%
  • Data Management and Algorithms5.5%
  • Advanced Clustering Algorithms Research5.2%
  • Network Security and Intrusion Detection3.1%
  • Data Mining Algorithms and Applications2.6%
  • Time Series Analysis and Forecasting2.4%
  • Other74.3%

Coauthors

All papers

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  1. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise

    Authors: Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu - http://www2.cs.uh.edu/~ceick/7363/Papers/dbscan.pdf, KDD 1996 cited by 28,029

  2. DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN

    Authors: Erich Schubert, Jörg Sander, Martin Ester, Hans Peter Kriegel, Xiaowei Xu - ACM Transactions on Database Systems, ACM Trans. Database Syst. 2017 cited by 2,625

  3. Density-Based Clustering Based on Hierarchical Density Estimates

    Authors: Ricardo J. G. B. Campello, Davoud Moulavi, Jörg Sander - Lecture notes in computer science, PAKDD (2) 2013 cited by 2,412

  4. OPTICS: Ordering Points To Identify the Clustering Structure

    Authors: Mihael Ankerst, Markus Breunig, Hans‐Peter Kriegel, Jörg Sander - ACM SIGMOD Record, SIGMOD Conference 1999 cited by 3,965

  5. LOF

    Authors: Markus Breunig, Hans‐Peter Kriegel, Raymond T. Ng, Jörg Sander - ACM SIGMOD Record 2000 cited by 5,181

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

    Authors: Ricardo J. G. B. Campello, Davoud Moulavi, Arthur Zimek, Jörg Sander - ACM Transactions on Knowledge Discovery from Data, ACM Trans. Knowl. Discov. Data 2015 cited by 857

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

    Authors: Guilherme Oliveira Campos, Arthur Zimek, Jörg Sander, Ricardo J. G. B. Campello, Barbora Micenková, Erich Schubert, Ira Assent, Michael E. Houle - Data Mining and Knowledge Discovery, Data Min. Knowl. Discov. 2016 cited by 732

  8. Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications

    Authors: Jörg Sander, Martin Ester, Hans-Peter Kriegel, Xiaowei Xu - Data Mining and Knowledge Discovery, Data Min. Knowl. Discov. 1998 cited by 1,468

  9. Density-based clustering

    Authors: Hans-Peter Kriegel, Peer Kröger, Jörg Sander, Arthur Zimek - Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, WIREs Data Mining Knowl. Discov. 2011 cited by 810

  10. Density-Based Clustering Validation

    Authors: Davoud Moulavi, Pablo A. Jaskowiak, Ricardo J. G. B. Campello, Arthur Zimek, Jörg Sander - SIAM International Conference on Data Mining, SDM 2014 cited by 262

  11. LOF: Identifying Density-Based Local Outliers

    Authors: Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng, Jörg Sander - http://www.dbs.informatik.uni-muenchen.de/Publikationen/Papers/LOF.pdf, SIGMOD Conference 2000 cited by 62

  12. Density-based clustering

    Authors: Ricardo J. G. B. Campello, Peer Kröger, Jörg Sander, Arthur Zimek - Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, WIREs Data Mining Knowl. Discov. 2019 cited by 116

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

    Authors: Arthur Zimek, Ricardo J. G. B. Campello, Jörg Sander - ACM SIGKDD Explorations Newsletter, SIGKDD Explor. 2013 cited by 273

  14. Subsampling for efficient and effective unsupervised outlier detection ensembles

    Authors: Arthur Zimek, Matthew Gaudet, Ricardo J. G. B. Campello, Jörg Sander - SIGKDD international conference on Knowledge discovery and data mining 2013 cited by 190

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

    Authors: Henrique O. Marques, Lorne Swersky, Jörg Sander, Ricardo J. G. B. Campello, Arthur Zimek - Data Mining and Knowledge Discovery, Data Min. Knowl. Discov. 2023 cited by 29

  16. Biological data annotation via a human-augmenting AI-based labeling system

    Authors: Douwe van der Wal, Iny Jhun, Israa Laklouk, Jeffrey J. Nirschl, Lara Richer, Rebecca Rojansky, Talent Theparee, Joshua Wheeler, Jörg Sander, Felix Y. Feng, Osama Mohamad, Silvio Savarese, Richard Socher, Andre Esteva - npj Digital Medicine, npj Digit. Medicine 2021 cited by 42

  17. Internal Evaluation of Unsupervised Outlier Detection

    Authors: Henrique O. Marques, Ricardo J. G. B. Campello, Jörg Sander, Arthur Zimek - ACM Transactions on Knowledge Discovery from Data, ACM Trans. Knowl. Discov. Data 2020 cited by 33

  18. Efficient Computation and Visualization of Multiple Density-Based Clustering Hierarchies

    Authors: Antônio Cavalcante Araújo Neto, Jörg Sander, Ricardo J. G. B. Campello, Mario A. Nascimento - IEEE Transactions on Knowledge and Data Engineering, IEEE Trans. Knowl. Data Eng. 2019 cited by 31

  19. A density-based algorithm for discovering clusters a density-based algorithm for discovering clusters in large spatial databases with noise

    Authors: Martin Ester, Hans‐Peter Kriegel, Jörg Sander, Xiaowei Xu - Knowledge Discovery and Data Mining 1996 cited by 1,137

  20. Semi-supervised Density-Based Clustering

    Authors: Levi Lelis, Jörg Sander - Ninth IEEE International Conference on Data Mining, ICDM 2009 cited by 100

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

    Authors: Jadson Castro Gertrudes, Arthur Zimek, Jörg Sander, Ricardo J. G. B. Campello - Data Mining and Knowledge Discovery, Data Min. Knowl. Discov. 2019 cited by 28

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

    Authors: Ricardo J. G. B. Campello, Davoud Moulavi, Arthur Zimek, Jörg Sander - Data Mining and Knowledge Discovery, Data Min. Knowl. Discov. 2013 cited by 83

  23. Mutual information for unsupervised deep learning image registration

    Authors: Bob D. de Vos, Bas H. M. van der Velden, Jörg Sander, Kenneth G. A. Gilhuijs, Marius Staring, Ivana Isgum - Medical Imaging 2020: Image Processing 2020 cited by 34

  24. OPTICS-OF: Identifying Local Outliers

    Authors: Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng, Jörg Sander - Lecture notes in computer science, PKDD 1999 cited by 185