Publications for Knowledge Discovery in Databases

  1. Kröger P., Zimek A.: Subspace Clustering Techniques, in: L. Liu and M. Tamer Özsu (eds.): Encyclopedia of Database Systems, 2009.
    EE (springerlink)

  2. Zimek A.: Correlation Clustering, in: SIGKDD Explorations, Vol. 11, No. 1, 2009, pp. 53-54.
    EE (SIGKDD Explorations)

  3. 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)

  4. Achtert A., Bernecker T., Kriegel H.-P., Schubert E., Zimek A.: ELKI in Time: ELKI 0.2 for the Performance Evaluation of Distance Measures for Time Series, Proc. 11th Int. Symp. on Spatial and Temporal Databases (SSTD 2009), Aalborg, Denmark, 2009, 436-440.
    Paper (pdf 432K)

  5. 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)

  6. 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)

  7. 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)

  8. Aßfalg J., Gong J., Kriegel H.-P.,Pryakhin A., Wei T., Zimek A.: Supervised Ensembles of Prediction Methods for Subcellular Localization, in: Journal of Bioinformatics and Computational Biology (JBCB), Vol. 7, Issue 2, (April 2009), 2009, pp. 269-285.
    EE (World Scientific), prediction server

  9. Kriegel H.-P., Kröger P., Zimek A.: Detecting Clusters in Moderate-to-high Dimensional Data: Subspace Clustering, Pattern-based Clustering, Correlation Clustering, (Tutorial), 34th Int. Conf. on Very Large Databases (VLDB 2008), Auckland, New Zealand, 2008.
    Slides (pdf 1.4M), EE (VLDB endowment)

  10. Kriegel H.-P., Kröger P., Zimek A.: Detecting Clusters in Moderate-to-high Dimensional Data: Subspace Clustering, Pattern-based Clustering, Correlation Clustering, (Tutorial), 14th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD 2008), Las Vegas, NV, 2008.
    Slides (pdf 1.4M)

  11. Kriegel H.-P., Renz M., Schubert M., Züfle A.: Statistical Density Prediction in Traffic Networks, Proc. 8th SIAM Conf. on Data Mining (SDM 2008), Atlanta, GA, 2008, pp. 692-703.
    Paper (pdf 1.03M)

  12. Kriegel H.-P., Schubert M., Zimek A.: Angle-Based Outlier Detection, Proc. 14th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'08), Las Vegas, NV, 2008, pp. 444-452.
    Paper (pdf 1.3M)

  13. Achtert E., Kriegel H.-P., Zimek A.: ELKI: A Software System for Evaluation of Subspace Clustering Algorithms, Proc. 20th Int. Conf. on Scientific and Statistical Database Management (SSDBM'08), Hong Kong, China, 2008, pp. 580-585.
    Paper (pdf 81K)

  14. Kriegel H.-P., Kröger P., Schubert E., Zimek A.: A General Framework for Increasing the Robustness of PCA-based Correlation Clustering Algorithms, Proc. 20th Int. Conf. on Scientific and Statistical Database Management (SSDBM'08), Hong Kong, China, 2008, pp. 418-435.
    Paper (pdf 255K)

  15. Kriegel H.-P., Kröger P., Zimek A.: Detecting Clusters in Moderate-to-high Dimensional Data: Subspace Clustering, Pattern-based Clustering, Correlation Clustering, (Tutorial), 12th Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD'08), Osaka, Japan, 2008.
    Slides (pdf 1.4M)

  16. Kriegel H.-P., Kröger P., Zimek A.: Detecting Clusters in Moderate-to-high Dimensional Data: Subspace Clustering, Pattern-based Clustering, Correlation Clustering, (Tutorial), 7th Int. Conf. on Data Mining (ICDM'07), Omaha, NE, 2007.
    Slides (pdf 2.11M)

  17. Aßfalg J., Kriegel H.-P., Pryakhin A., Schubert M.: Multi-Represented Classification based on Confidence Estimation, Proc. 11th Pacific-Asia Conf. on Advances in Knowledge Discovery and Data Mining (PAKDD 2007), in: LNCS, Nanjing, China, 2007, pp. 23-34.
    Paper (pdf 198K)

  18. Achtert E., Böhm C., Kriegel H.-P., Kröger P., Zimek A.: Robust, Complete, and Efficient Correlation Clustering, Proc. 7th SIAM Int. Conf. on Data Mining (SDM'07), Minneapolis, MN, 2007, pp. 413-418.
    Paper (pdf 217K)

  19. Kriegel H.-P., Borgwardt K. M., Kröger P., Pryakhin A., Schubert M., Zimek A.: Future Trends in Data Mining, in: Data Mining and Knowledge Discovery, DOI: 10.1007/s10618-007-0067-9, 2007. Springer's Open Choice

  20. Achtert E., Böhm C., Kriegel H.-P., Kröger P., Zimek A.: On Exploring Complex Relationships of Correlation Clusters, Proc. 19th Int. Conf. on Scientific and Statistical Database Management (SSDBM'07), Banff, Canada, 2007.
    Paper (pdf 357K)

  21. Achtert E., Böhm C., Kriegel H.-P., Kröger P., Müller-Gormann I., Zimek A.: Detection and Visualization of Subspace Cluster Hierarchies, Proc. 12th Int. Conf. on Database Systems for Advance Applications (DASFAA'07), Bangkok, Thailand, 2007, pp. 152-163.
    Paper (pdf 239K)

  22. Vishwanathan S. V. N., Borgwardt K. M., Schraudolph N.: Fast Computation of Graph Kernels, Proc. 20th Annual Conf. on Neural Information Processing Systems (NIPS 2006), Vancouver, B.C., Canada, 2007, pp. 1449-1456.
    Paper (pdf 419K)

  23. Gretton A., Borgwardt K. M., Rasch M., Schölkopf B., Smola A.: A Kernel Method for the Two-Sample-Problem, (full oral presentation), Proc. 20th Annual Conf. on Neural Information Processing Systems (NIPS 2006), Vancouver, B.C., Canada, 2007, pp. 513-520.
    Paper (pdf 357K)

  24. Huang J., Smola A., Gretton A., Borgwardt K. M., Schölkopf B.: Correcting Sample Selection Bias by Unlabeled Data, Proc. 20th Annual Conf. on Neural Information Processing Systems (NIPS 2006), Vancouver, B.C., Canada, 2007, pp. 601-608.
    Paper (pdf 386K)

  25. Gretton A., Borgwardt K. M., Rasch M., Schölkopf B., Smola A.: A Kernel Method for the Two-Sample-Problem, (full oral presentation), Proc. 20th Annual Conf. on Neural Information Processing Systems (NIPS 2006), Vancouver, B.C., Canada, 2007, pp. 513-520.
    Paper (pdf 357K)

  26. Huang J., Smola A., Gretton A., Borgwardt K. M., Schölkopf B.: Correcting Sample Selection Bias by Unlabeled Data, Proc. 20th Annual Conf. on Neural Information Processing Systems (NIPS 2006), Vancouver, B.C., Canada, 2007, pp. 601-608.
    Paper (pdf 386K)

  27. Borgwardt K. M., Vishwanathan S. V. N., Schraudolph N., Kriegel H.-P.: Graph Kernels for disease outcome prediction from protein-protein interaction, Proc. Pacific Symposium on Biocomputing (PSB'07), Wailea, Maui, 2007, pp. 4-15.
    Paper (pdf 397K)

  28. Vishwanathan S. V. N., Borgwardt K. M., Schraudolph N.: Fast Computation of Graph Kernels, Proc. 20th Annual Conf. on Neural Information Processing Systems (NIPS 2006), Vancouver, B.C., Canada, 2007, pp. 1449-1456.
    Paper (pdf 419K)

  29. Gretton A., Borgwardt K. M., Rasch M., Schölkopf B., Smola A.: A Kernel Method for the Two-Sample-Problem, (full oral presentation), Proc. 20th Annual Conf. on Neural Information Processing Systems (NIPS 2006), Vancouver, B.C., Canada, 2007, pp. 513-520.
    Paper (pdf 357K)

  30. Huang J., Smola A., Gretton A., Borgwardt K. M., Schölkopf B.: Correcting Sample Selection Bias by Unlabeled Data, Proc. 20th Annual Conf. on Neural Information Processing Systems (NIPS 2006), Vancouver, B.C., Canada, 2007, pp. 601-608.
    Paper (pdf 386K)

  31. Brecheisen S., Kriegel H.-P., Kröger P., Pfeifle M., Schubert M., Zimek A.: Density-Based Data Analysis and Similarity Search, in: Petrushin V. A., Khan L. (eds.): Multimedia Data Mining and Knowledge Discovery, Springer, 2007, pp. 94-115.
    Paper (pdf 566K)

  32. 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)

  33. 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.

  34. Borgwardt K. M., Kriegel H.-P., Wackersreuther P.: Pattern Mining in Frequent Dynamic Subgraphs, Proc. IEEE Int. Conf. on Data Mining (ICDM'06), Hong Kong, 2006, pp. 818-822.
    Paper (pdf 388K)

  35. Achtert E., Böhm C., Kriegel H.-P., Kröger P., Müller-Gorman I., Zimek A.: Finding Hierarchies of Subspace Clusters, Proc. 10th European Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'06), Berlin, Germany, 2006.
    Paper (pdf 95K)

  36. Aßfalg J., Borgwardt K. M., Kriegel H.-P.: 3DString: A Feature String Kernel for 3D Object Classification on Voxelized Data, Proc. ACM 15th Conf. on Information and Knowledge Management (CIKM'06), Arlington, VA, 2006, pp. 198-207.
    Paper (pdf 111K)

  37. Achtert E., Böhm C., Kriegel H.-P., Kröger P., Zimek A.: Deriving Quantitative Models for Correlation Clusters, Proc. ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'06), Philadelphia, PA, 2006, pp. 4-13.
    Paper (pdf 327K)

  38. Borgwardt K. M., Gretton A., Rasch M., Kriegel H.-P., Schölkopf B., Smola A. J.: Integrating structured biological data by Kernel Maximum Mean Discrepancy, Proc. 14th Annual Int. Conf. on Intelligent Systems for Molecular Biology (ISMB'06), Fortaleza, Brazil, 2006, in: Bioinformatikcs Vol 22, No. 14, pp. 49-57.
    Abstract (pdf)

  39. Baumgartner C., Böhm C., Baumgartner D., Marini G., Weinberger K., Olgemöller B., Liebl B., Roscher A. A.: Supervised machine learning techniques for the classification of metabolic disorders in newborns, in: Haux R., Kulikowski C. (eds.) IMIA Yearbook of Medical Informatics, 2006.

  40. Borgwardt K. M., Boettger S., Kriegel H.-P.: VGM: Visual Graph Mining, demo paper, Proc. ACM SIGMOD Int. Conference on Management of Data, Chicago, ILL, 2006, pp. 733-735.

  41. Vishwanathan S.V., Borgwardt K. M., Guttman O., Smola A. J.: Kernel Extrapolation, in: Neurocomputing, Vol. 6, Issues 7-9, March 2006, pp. 721-729.
    Paper (pdf)

  42. Borgwardt K. M., Vishwanathan S. V., Kriegel H.-P.: Class prediction from time series gene expression profiles using dynamical systems kernels, Proc. Pacific Symp. on Biocomputing (PSB), Maui, Hawaii, 2006, pp. 547-558.
    Paper (pdf 148K)

  43. 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)

  44. Kriegel H.-P, Pryakhin A., Schubert M.: An EM-Approach for Clustering Multi-Instance Objects, Proc. 10th Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD 2006), Singapore, 2006.
    Paper (pdf 383K)

  45. Achtert E., Kriegel H.-P., Pryakhin A., Schubert M.: Clustering Multi-Represented Objects Using Combination Trees , Proc. 10th Pacific-Asia Conf. on Knowledge Discovery and Data Mining (PAKDD 2006), Singapore, 2006.
    Paper (pdf 358K)

  46. Kriegel H.-P., Schubert M.: Advanced Prototype Machines: Exploring Prototypes for Classification, in Proc. 6th SIAM Conf. on Data Mining (SDM 06), Bethesda, MD, 2006, pp. 176-187.
    Paper (pdf 526K)

  47. Brecheisen S., Gruber M., Kriegel H.-P., Schubert M.: VICO: Visualizing Connected Object Orderings, Demonstration, 10th Int. Conf. on Extending Database Technology (EDBT 2006), Munich, Germany, in: Lecture Notes in Computer Science (LNCS), Springer, Vol. 3896, pp. 1151-1154, 2006.
    Paper (pdf 146K)

  48. 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)

  49. 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)

  50. Kriegel H.-P., Kröger P., Pryakhin A., Schubert M.: Effective and Efficient Distributed Model-based Clustering, Proc. 5th IEEE Int. Conf. on Data Mining (ICDM'05), Houston, TX, 2005, pp. 258-265.
    Paper (pdf 214K)

  51. Huang Y., Yu K., Schubert M., Yu S., Kriegel H.-P.: Hierarchy-Regularized Latent Semantic Indexing, Proc. 5th IEEE Int. Conf. on Data Mining (ICDM'05), Houston, TX, 2005, pp. 178-185.
    Paper (pdf 274K)

  52. Borgwardt K., Kriegel H.-P.: Shortest-path kernels on graphs, Proc. 5th IEEE Int. Conf. on Data Mining (ICDM'05), Houston, TX, 2005, pp. 74-81.
    Paper (pdf 290K)

  53. Achtert E., Kriegel H.-P., Pryakhin A., Schubert M.: Hierarchical Density-Based Clustering for Multi-Represented Objects, Workshop on Mining Complex Data (MCD 2005), 5th Int. Conf. on Data Mining, Houston, TX, 2005.
    Paper (pdf 617K)

  54. Kriegel H.-P., Pfeifle M.: Density-based clustering of uncertain data, Proc. 11th Int. Conf. on Knowledge Discovery and Data Mining (KDD'05), Chicago, IL, 2005, pp. 672-677.

  55. Borgwardt K. M., Kriegel H.-P.: Kernel Methods for Protein Function Prediction, short review, Proc. ISMB-satellite "Automated Function Prediction" (AFP 2005), Detroit, MI, 2005.
    Paper (pdf 594K)

  56. Borgwardt K. M., Ong C. S., Schönauer S., Vishwanathan S. V. N., Smola A. J., Kriegel H.-P.: Protein Function Prediction via Graph Kernels , Proc. "Intelligent Systems in Molecular Biology" (ISMB 2005), Detroit, MI, 2005, pp. 47-56.
    Paper pdf

  57. Borgwardt K. M., Guttman O., Vishwanathan S. V. N., Smola A. J.: Joint Regularization, Proc. "European Symp. on Artificial Neural Networks" (ESANN 2005), Brügge, Belgium, 2005.
    Paper (pdf 306K)

  58. Kriegel H.-P., Pryakhin A., Schubert M.: Multi-represented kNN-Classification for Large Class Sets, Proc. 10th Int. Conf. on Database Systems for Advanced Applications (DASFAA'05), Bejing, China, 2005, pp. 511-522.
    Paper (pdf 350K)

  59. Baumgartner C., Gautsch K., Böhm C., Felber S.: Functional cluster analysis of CT perfusion maps: A new tool for diagnosis of acute stroke?, in J. Digit Imaging, Vol. 18, 2005, pp. 219-226.

  60. Baumgartner C., Böhm C., Baumgartner D.: Modelling of classification rules on metabolic patterns including machine learning and expert knowledge, in J. Biomed Inform., Vol. 38, 2005, pp. 89-98.

  61. Baumgartner C., Baumgartner D., Böhm C.: Modelling of classification rules on metabolic patterns including machine learning and expert knowledge, (Abstract + poster), Bioinformatics 2004, Linköping, Sweden, 2004.

  62. Baumgartner C., Böhm C., Baumgartner D., Marini G., Weinberger K., Olgemöller B., Liebl B., Roscher A.A.: Supervised machine learning techniques for the classification of metabolic disorders in newborns, Proc. Bioinformatics 2004, Linköping, Sweden, Vol. 20, No. 17, 2004, pp. 2985-2996.

  63. Januzaj E., Kriegel H.-P., Pfeifle M.: Scalable Density-Based Distributed Clustering, Proc. 8th European Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'04), Pisa, Italy, 2004, in: Lectures Notes in Computer Science, Springer, Vol. 3202, 2004, pp. 231-244.
    Paper (pdf 216K)

  64. Baumgartner C., Kailing K., Kriegel H.-P., Kröger P., Plant C.: Subspace Selection for Clustering High-Dimensional Data, Proc. 4th IEEE Int. Conf. on Data Mining (ICDM'04), Brighton, UK, 2004, pp. 11-18.
    Paper (pdf 333K)

  65. 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)

  66. 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)

  67. Kailing K., Kriegel H.-P., Schönauer S.: Content-Based Image Retrieval Using Multiple Representations, Proc. 8th Int. Conf. on Knowledge-Based Intelligent Information and Engineering Systems (KES'04), Wellington, New Zealand, LNAI 3214, 2004, pp. 982-988.
    Paper (pdf 406K)

  68. Ester M., Kriegel H.-P., Schubert M.: Accurate and Efficient Crawling for Relevant Websites, Proc. 30th Int. Conf. on Very Large Databases (VLDB'04), Toronto, Canada, 2004, pp. 396-407.
    Paper (pdf 450K)

  69. Böhm C., Kailing K., Kröger P., Kriegel H.-P.: Immer größere und komplexere Datenmengen: Herausforderungen für Clustering-Algorithmen, in: Datenbank-Spektrum, Vol. 4, No. 9, 2004, pp. 11-17.
    Paper (pdf 241K)

  70. 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)

  71. 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)

  72. Schubert M., Pryakhin A., Kröger P., Kriegel H.-P.: Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects, Proc. SIAM Int. Conf. on Data Mining (SDM'04), Lake Buena Vista, FL, 2004, pp. 102-114.
    Paper (pdf 347K)

  73. Kröger P., Kriegel H.-P., Kailing K.: Density-Connected Subspace Clustering for High-Dimensional Data, Proc. SIAM Int. Conf. on Data Mining (SDM'04), Lake Buena Vista, FL, 2004, pp. 246-257.
    Paper (pdf 341K)

  74. Brecheisen S., Kriegel H.-P., Kröger P., Pfeifle M.: Visually Mining Through Cluster Hierarchies, Proc. SIAM Int. Conf. on Data Mining (SDM'04), Lake Buena Vista, FL, 2004, pp. 400-412.
    Paper (pdf 753K)

  75. Baumgartner C., Baumgartner D., Böhm C.: Classification on high dimensional metabolic data: Phenylketonuria as an example, Proc. 2nd Int. Conf. on Biomedical Engineering (BioMED 2004), Innsbruck, Austria, 2004, pp. 357-360.

  76. Januzaj E., Kriegel H.-P., Pfeifle M.: A Quality Measure for Distributed Clustering, Proc. IASTED Int. Conf. on Databases and Applications (DBA 2004), Innsbruck, Austria, 2004, pp. 133-138.
    Paper (pdf 374K)

  77. Januzaj E., Kriegel H.-P., Pfeifle M.: DBDC: Density Based Distributed Clustering, Proc. 9th Int. Conf. on Extending Database Technology (EDBT 2004), Heraklion, Greece, 2004, pp. 88-105.
    Paper (pdf 429K)

  78. Kriegel H.-P., Schubert M.: Classification of Websites as Sets of Feature Vectors, Proc. IASTED Int. Conf. on Databases and Applications (DBA 2004), Innsbruck, Austria, 2004, pp. 127-132.
    Paper (pdf 328K)

  79. Yu K., Schwaighofer A., Tresp V., Xu X., Kriegel H.-P.: Probabilistic Memory-based Collaborative Filtering, in: IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 16, No. 1, 2004, pp. 56-69.
    Abstract

  80. Böhm C., Krebs F.: The k-Nearest Neighbor Join: Turbo Charging the KDD Process, in: Knowledge and Information Systems (KAIS), Vol. 6, No. 6, 2004, pp. 728-749.
    Paper (pdf 367K)

  81. Böhm C., Krebs F.: Supporting KDD Applications by the k-Nearest Neighbor Join, Proc. 14th Int. Conf. on Database and Expert Systems Applications (DEXA), Prague, Czech Republic, 2003, in: Lecture Notes in Computer Science, Vol. 2736, Springer, 2003, pp. 504-516.
    Paper (pdf 256K)

  82. Januzaj E., Kriegel H.-P., Pfeifle M.: Towards Effective and Efficient Distributed Clustering, Proc. Int. Workshop on Clustering Large Data Sets, 3rd Int. Conf. on Data Mining (ICDM 2003), Melbourne, FL, 2003, pp. 49-58.
    Paper (pdf 441K)

  83. Kailing K., Kriegel H.-P., Kröger P., Wanka S.: Ranking Interesting Subspaces for Clustering High Dimensional Data, Proc. 7th European Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'03), Cavtat-Dubrovnic, Croatia, 2003, in: Lecture Notes in Artificial Intelligence (LNAI), Vol. 2838, 2003, pp. 241-252.
    Paper (pdf 353K)

  84. Kriegel H.-P., Schönauer S.: Similarity Search in Structured Data, Proc. 5th Int. Conf. on Data Warehousing and Knowledge Discovery (DaWaK'03), Prague, Czech Republic, 2003, in: Lecture Notes in Computer Science (LNCS), Vol. 2737, 2003, pp. 309-319.
    Paper (pdf 267K)

  85. 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)

  86. Yu K., Xu X., Ester M., Kriegel H.-P.: Feature Weighting and Instance Selection for Collaborative Filtering: An Information-Theoretic Approach, in: Knowledge and Information Systems (KAIS), Vol. 5, No. 2 Springer, Vol. 5, No. 2, 2003, pp. 201-224.
    Abstract

  87. Böhm C.: Powerful Database Primitives to Support High Performance Data Mining, (Tutorial) 2nd IEEE Int. Conf. on Data Mining (ICDM), Maebashi City, Japan, 2002.
    Paper (pdf 974K)

  88. Böhm C., Krebs F.: High Performance Data Mining Using the Nearest Neighbor Join, Proc. 2nd IEEE Int. Conf. on Data Mining (ICDM), Maebashi City, Japan, 2002, pp. 43-50.
    Paper (pdf 293K)

  89. Böhm C.: Similarity Search and Data Mining: Database Techniques Supporting Next Decade's Applications, (Keynote Speech) Proc. 4th Int. Conf. on Information Integration and Web-based Applications & Services (IIWAS), Bandung, Indonesia 2002.
    Paper (pdf 207K)

  90. Ester M., Kriegel H.-P., Schubert M.: Web Site Mining: A new way to spot Competitors, Customers and Suppliers in the World Wide Web, Proc. 8th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'02), Edmonton, Canada, 2002, pp. 249-258.
    Paper (pdf 150K)

  91. Böhm C., Krebs F., Kriegel H.-P.: Optimal Dimension Order: A Generic Technique for the Similarity Join, Proc. 4th Int. Conf. on Data Warehousing and Knowledge Discovery (DaWaK'02), Aix-en-Provence, France, 2002, pp. 135-149.
    Paper (pdf 258K)

  92. Yu K., Xu X., Tao J., Ester M., Kriegel H.-P.: Instance Selection Techniques for Memory-Based Collaborative Filtering, Proc. 2nd SIAM Int. Conf. on Data Mining (SDM'02), Arlington, VA, 2002.
    Paper (pdf 485K)

  93. Yu K., Wen Z., Xu X., Ester M.: Feature Weighting and Instance Selection for Collaborative Filtering, Proc. 2nd Int. Workshop on Management of Information on the Web - Web Data and Text Mining (MIW'01), 2001, pp. 285-290.
    Paper (pdf 111K)

  94. Yu K., Xu X., Ester M., Kriegel H.-P.: Selecting Relevant Instances for Efficient and Accurate Collaborative Filtering, Proc. ACM 10th Int. Conf. on Information and Knowledge Management (CIKM'01), 2001, pp. 247-254.
    Paper (pdf 366K)

  95. 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)

  96. Böhm C., Kriegel H.-P., Seidl T.: Determining the Convex Hull in Large Multidimensional Databases, Proc. Int. Conf. on Data Warehousing and Knowledge Discovery (DaWaK 2001), Munich, Germany, 2001, pp. 294-306.
    Paper (pdf 235K)

  97. Böhm C., Kriegel H.-P., Seidl T.: Adaptable Similarity Search Using Vector Quantization, Proc. Int. Conf. on Data Warehousing and Knowledge Discovery (DaWaK 2001), Munich, Germany, 2001, pp. 317-327.
    Paper (pdf 131K)

  98. 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)

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

  100. Böhm C., Braunmüller B., Krebs F., Kriegel H.-P.: Epsilon Grid Order: An Algorithm for the Similarity Join on Massive High-Dimensional Data, Proc. ACM SIGMOD Int. Conf. on Managment of Data (SIGMOD'01), Santa Barbara, CA, 2001, pp. 379-388.
    Paper (pdf 163K)

  101. Böhm C., Kriegel H.-P.: A Cost Model and Index Architecture for the Similarity Join, Proc. 17th Int. Conf. on Data Engineering (ICDE), Heidelberg, Germany, 2001, pp. 411-420.
    Paper (pdf 167K)

  102. Böhm C.: The Similarity Join: A Powerful Database Primitive for High Performance Data Mining, (Tutorial), 17th Int. Conf. on Data Engineering (ICDE 2001), Heidelberg, Germany, 2001, p. XVII.

  103. Braunmüller B., Ester M., Kriegel H.-P., Sander J.: Multiple Similarity Queries: A Basic DBMS Operation for Mining in Metric Databases, in: Special Issue on "Best Papers of ICDE 2000", IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 13, No. 1, 2001, pp. 79-95.
    Abstract

  104. Ester M., Sander J.: Knowledge Discovery in Databases: Techniken und Anwendungen, (in German), Springer textbook, Springer, September 2000, ISBN: 3-540-67328-8.
    Paper (pdf 10K)

  105. 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)

  106. 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)

  107. Böhm C., Braunmüller B., Kriegel H.-P.: The Pruning Power: Theory and Heuristics for Mining Databases with Multiple k-Nearest-Neighbor Queries, Proc. Int. Conf. on Data Warehousing and Knowledge Discovery (DaWaK 2000), Greenwich, U.K., 2000, pp. 372-381.
    Paper (pdf 82K)

  108. Ankerst M., Ester M., Kriegel H.-P.: Towards an Effective Cooperation of the Computer and the User for Classification, Proc. ACM SIGKDD Int. Conf. on Knowledge Discovery & Data Mining (KDD 2000), Boston, MA, 2000, pp. 179-188.
    Paper (pdf 1.52M)

  109. 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)

  110. Braunmüller B., Ester M., Kriegel H.-P., Sander J.: Efficiently Supporting Multiple Similarity Queries for Mining in Metric Databases, Proc. 16th Int. Conf. on Data Engineering (ICDE 2000), San Diego, CA, 2000, pp. 256-267.
    Paper (pdf 142K)

  111. Ester M., Frommelt A., Kriegel H.-P., Sander J.: Spatial Data Mining: Database Primitives, Algorithms and Efficient DBMS Support, accepted for Special Issue on: "Integration of Data Mining with Database Technology, Data Mining and Knowledge Discovery, an International Journal, Kluwer Academic Publishers, Vol. 4, 2000, pp. 193-216.
    Abstract (pdf 5K)

  112. Ankerst M., Elsen C., Ester M., Kriegel H.-P.: Perception-Based Classification, in: Informatica, An International Journal of Computing and Informatics, Vol. 23, No. 4, ISSN 0350-5596, 1999, pp. 493-499.

  113. 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)

  114. Ester M., Kriegel H.-P., Sander J.: Knowledge Discovery in Spatial Databases, invited paper at 23rd German Conf. on Artificial Intelligence (KI '99), Bonn, Germany, in: Lecture Notes in Computer Science, Vol. 1701, 1999, pp. 61-74.
    Paper (pdf 179K)

  115. Ankerst M., Elsen C., Ester M., Kriegel H.-P.: Visual Classification: An Interactive Approach to Decision Tree Construction, Proc. 5th Int. Conf. on Knowledge Discovery and Data Mining (KDD'99), San Diego, CA, 1999, pp. 392-396.
    Paper (postscript 3,53MB), Paper (pdf 93K)

  116. Berchtold S., Böhm C., Kriegel H.-P., Michel U.: Implementation of Multidimensional Index Structures for Knowledge Discovery in Relational Databases, Proc. Int. Conf. on Data Warehousing and Knowledge Discovery (DaWaK'99), Florence, Italy 1999, in: Lecture Notes in Computer Science, Vol. 1676, Springer, 1999, pp. 261-270.
    Paper (postscript 1,36MB), Paper (pdf 223K)

  117. Böhm C., Kriegel H.-P.: Efficient Bulk Loading of Large High-Dimensional Indexes, Proc. Int. Conf. on Data Warehousing and Knowledge Discovery (DaWaK'99), Florence, Italy, 1999, in: Lecture Notes in Computer Science, Vol. 1676, Springer, 1999, pp. 251-260.
    Paper (postscript 7,76MB), Paper (pdf 1,28MB)

  118. 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.

  119. Ester M., Gundlach S., Kriegel H.-P., Sander J.: Database Primitives for Spatial Data Mining, Proc. 8. GI-Fachtagung Datenbanksysteme in Büro, Technik und Wissenschaft (BTW'99) (Int. Conf. on Databases in Office, Engineering and Science), Freiburg, Germany, 1999, pp. 137-150.
    Paper (pdf 155K)

  120. 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)

  121. 1998

    Ankerst M., Berchtold S., Keim D. A.: Similarity Clustering of Dimensions for an Enhanced Visualization of Multidimensional Data, Proc. Symp. on Information Visualization, Phoenix, AZ, 1998.
    Paper (postscript 2.82M)

  122. Ester M., Frommelt A., Kriegel H.-P., Sander J.: Algorithms for Characterization and Trend Detection in Spatial Databases, Proc. 4th Int. Conf. on Knowledge Discovery and Data Mining (KDD'98), New York City, NY, 1998, pp. 44-50.
    Paper (postscript 2.3M), (pdf 153K)

  123. 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)

  124. 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)

  125. 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)

  126. Ester M., Wittmann R.: Incremental Generalization for Mining in a Data Warehousing Environment, Proc. Int. Conf. on Extending Database Technology, Valencia, Spain, 1998, pp. 135-149.
    Paper (postscript 1.09M)

  127. 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)

  128. 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.

  129. 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)

  130. 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)