Publications for Density-Based Cluster- and Outlier Detection

  1. Kriegel H.-P., Kröger P., Schubert E., Zimek A.: LoOP: Local Outlier Probabilities, Proc. ACM 18th Conf. on Information and Knowledge Management (CIKM'09), Hong Kong, China, 2009.
    Paper (pdf 573K)

  2. Kriegel H.-P., Kröger P., Zimek A.: Clustering High-Dimensional Data: A Survey on Subspace Clustering, Pattern-based Clustering, and Correlation Clustering, in: ACM Transactions on Knowledge Discovery from Data (TKDD), Vol. 3, Issue 1, Article No. 1, 2009, pp. 1-58.
    EE (ACM)

  3. Kriegel H.-P., Kröger P., Schubert E., Zimek A.: Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data, Proc. 13th Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD 2009), Bangkok, Thailand, 2009, pp. 831-838.
    Paper (pdf 313K)

  4. Kriegel H.-P., Kröger P., Zimek A.: Outlier Detection Techniques, (Tutorial), 13th Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD 2009), Bangkok, Thailand, 2009.
    Slides (pdf 104K)

  5. Kriegel H.-P., Pryakhin A., Schubert M., Zimek A.: COSMIC: Conceptually Specified Multi-Instance Clusters, Proc. IEEE 6th Int. Conf. on Data Mining (ICDM'06), Hong Kong, China, 2006, pp. 917-921.
    Paper (pdf 191K)

  6. Kailing K., Kriegel H.-P., Pfeifle M., Schönauer S.: Extending Metric Index Structures for Efficient Range Query Processing, in: Knowledge and Information Systems (KAIS), Vol. 10, No. 2, 2006, pp. 211-227.
    The original publication is available at www.springerlink.com.

  7. Brecheisen S., Kriegel H.-P., Pfeifle M.: Multi-Step Density-Based Clustering, in: Knowledge and Information Systems (KAIS), Vol. 9, No. 3, 2006.
    The original publication is available at www.springerlink.com.
    Paper (pdf 719K)

  8. Achtert E., Böhm C., Kröger P.: DeLiClu: Boosting Robustness, Completeness, Usability, and Efficiency of Hierarchical Clustering by a Closest Pair Ranking, Proc. 10th Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD'06), Singapore, 2006, pp. 119-128.
    Paper (pdf 282K)

  9. Brecheisen S., Kriegel H.-P., Pfeifle M.: Parallel Density-Based Clustering of Complex Objects, Proc. 10th Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD'06), Singapore, 2006, in: Lecture Notes in Artificial Intelligence (LNAI), Springer, Vol. 3918, pp. 179-188, 2006.
    Paper (pdf 285K)

  10. Achtert E., Böhm C., Kriegel H.-P., Kröger P.: Online Hierarchical Clustering in a Data Warehouse Environment, Proc. 5th IEEE Int. Conf. on Data Mining (ICDM'05), Houston, TX, 2005, pp. 10-17.
    Paper (pdf 224K)

  11. Kriegel H.-P., Kröger P., Renz M., Wurst S.: A Generic Framework for Efficient Subspace Clustering of High-Dimensional Data, Proc. 5th IEEE Int. Conf. on Data Mining (ICDM'05), Houston, TX, 2005, pp. 250-257.
    Paper (pdf 210K)

  12. Böhm C., Kriegel H.-P., Kröger P., Linhart P.: Selectivity Estimation of High Dimensional Window Queries Via Clustering, Proc. 9th Int. Symp. on Spatial and Temporal Databases (SSTD'05), Angra dos Reis, Brazil, 2005, pp. 1-18.
    Paper (pdf 278K)

  13. Brecheisen S., Kriegel H.-P., Pfeifle M.: Efficient Density-Based Clustering of Complex Objects, Proc. 4th IEEE Int. Conf. on Data Mining (ICDM'04), Brighton, UK, 2004, pp. 43-50.
    Paper (pdf 114K)

  14. Böhm C., Kailing K., Kriegel H.-P., Kröger P.: Density Connected Clustering with Local Subspace Preferences, Proc. 4th IEEE Int. Conf. on Data Mining (ICDM'04), Brighton, UK, 2004, pp. 27-34.
    Paper (pdf 276K)

  15. Kailing K., Kriegel H.-P., Pfeifle M., Schönauer S.: Efficient Indexing of Complex Objects for Density-based Clustering, Proc. 5th Int. Workshop on Multimedia Data Mining (MDM/KDD), Seattle, WA, 2004, pp. 28-37.
    Paper (pdf 427K)

  16. Kailing K., Kriegel H.-P., Pryakhin A., Schubert M.: Clustering Multi-Represented Objects with Noise, Proc. 8th Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD'04), Sydney, Australia, 2004, pp. 394-403.
    Paper (pdf 702K)

  17. Böhm C., Kailing K., Kröger P., Zimek A.: Computing Clusters of Correlation Connected Objects, Proc. ACM SIGMOD Int. Conf. on Management of Data, Paris, France, 2004, pp. 455-466.
    Paper (pdf 813K)

  18. Kriegel H.-P., Kröger P., Gotlibovich I.: Incremental OPTICS: Efficient Computation of Updates in a Hierarchical Cluster Ordering, 5th Int. Conf. on Data Warehousing and Knowledge Discovery (DaWaK'03), Prague, Czech Republic, 2003, pp. 224-233.
    Paper (pdf 135K)

  19. Ester M., Kriegel H.-P., Sander J.: Algorithms and Applications for Spatial Data Mining, in: Geographic Data Mining and Knowledge Discovery, Research Monographs in GIS, Taylor and Francis, 2001, pp. 160-187.
    Paper (pdf 387K)

  20. Breunig M. M., Kriegel H.-P., Kröger P., Sander J.: Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering, Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'01), Santa Barbara, CA, 2001, pp. 79-90.
    Paper (pdf 421K)

  21. Breunig M. M.: Quality Driven Database Mining, Ph.D. thesis, University of Munich, Shaker Verlag, Aachen, ISBN 3-8265-8559-3, 2001.

  22. Böhm C., Braunmüller B., Breunig M., Kriegel H.-P.: High Performance Clustering Based on the Similarity Join, Proc. 9th Int. Conf. on Information and Knowledge Management (CIKM 2000), Washington, DC, 2000, pp. 298-313.
    Paper (pdf 151K)

  23. Breunig M., Kriegel H.-P., Sander J.: Fast Hierarchical Clustering Based on Compressed Data and OPTICS, Proc. 4th European Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD 2000), Lyon, France, 2000, pp. 232-242.
    Paper (pdf 488K)

  24. Breunig M. M., Kriegel H.-P., Ng R., Sander J.: LOF: Identifying Density-Based Local Outliers, Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD 2000), Dallas, TX, 2000, pp. 93-104.
    Paper (pdf 312K)

  25. Breunig M. M., Kriegel H.-P., Ng R., Sander J.: OPTICS-OF: Identifying Local Outliers, Proc. 3rd European Conf. on Principles of Data Mining and Knowledge Discovery (PKDD'99), Prague, Czech Republic, 1999, in: Lecture Notes in Computer Science, Springer, Vol. 1704, 1999, pp. 262-270.
    Paper (pdf 70K)

  26. Xu X., Jäger J., Kriegel H.-P.: A Fast Parallel Clustering Algorithm for Large Spatial Databases, in: Data Mining and Knowledge Discovery, an International Journal, Vol. 3, No. 3, Kluwer Academic Publishers, 1999, pp. 263-290.

  27. Ankerst M., Breunig M. M., Kriegel H.-P., Sander J.: OPTICS: Ordering Points To Identify the Clustering Structure, Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'99), Philadelphia, PA, 1999, pp. 49-60.
    Paper (pdf 257K)

  28. Ester M., Kriegel H.-P., Sander J., Wimmer M., Xu X.: Incremental Clustering for Mining in a Data Warehousing Environment, Proc. 24th Int. Conf. on Very Large Data Bases (VLDB'98), New York City, NY, 1998, pp. 323-333.
    Paper (postscript 1M), (pdf 158K)

  29. Sander J., Ester M., Kriegel H.-P., Xu X.: Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and its Applications, in: Data Mining and Knowledge Discovery, an Int. Journal, Kluwer Academic Publishers, Vol. 2, No. 2, 1998, pp. 169-194.
    Abstract (22K)

  30. Xu X., Ester M., Kriegel H.-P., Sander J.: A Distribution-Based Clustering Algorithm for Mining in Large Spatial Databases, Proc. 14th Int. Conf. on Data Engineering (ICDE'98), Orlando, FL, 1998, pp. 324-331.
    Paper (postscript 923K)

  31. Ester M., Kriegel H.-P., Sander J., Xu X.: Clustering for Mining in Large Spatial Databases, in: Special Issue on Data Mining, KI-Journal, ScienTec Publishing, No. 1, 1998, pp. 18-24.
    Paper (postscript 967K)

  32. 1997

    Xu X., Ester M., Kriegel H.-P., Sander J.: Clustering and Knowledge Discovery in Spatial Databases, in: Vistas in Astronomy, Elsevier Science Ltd., Vol. 41, No. 3, 1997, pp. 397-403.

  33. Ester M., Kriegel H.-P., Sander J., Xu X.: Density-Connected Sets and their Application for Trend Detection in Spatial Databases, Proc. 3rd Int. Conf. on Knowledge Discovery and Data Mining (KDD'97), Newport Beach, CA, 1997, pp. 10-15.
    Paper (postscript 1.8M)

  34. Ester M., Kriegel H.-P., Sander J.: Spatial Data Mining: A Database Approach, Proc. 5th Int. Symposium on Large Spatial Databases (SSD'97), Berlin, Germany, 1997, pp. 47-66.
    Paper (postscript 977k)

  35. Ester M., Kriegel H.-P., Sander J., Xu X.: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise, Proc. 2nd Int. Conf. on Knowledge Discovery and Data Mining (KDD'96), Portland, OR, 1996, pp. 226-231.
    Abstract, Paper (pdf 82k), Paper (postscript 163k)

  36. Brinkhoff T., Kriegel H.-P.: The Impact of Global Clustering on Spatial Database Systems, Proc. 20th Int. Conf. on Very Large Data Bases (VLDB'94), Santiago, Chile, 1994, pp. 168-179.
    Abstract, Paper (postscript 450k)