Neil's Bibliography on
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  1. Uysal and H. A. Güvenir
    Regression by Feature Projections
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 568-573, Springer, September 15-18 1999.

  2. A. A. Freitas
    On Objective Measures of Rule Suprisingness
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 1-9, Springer, September 23-26 1998.

  3. A. A. Freitas
    Scalable, High-Performance Data Mining with Parallel Processing
    Lecture Notes in Computer Science, Vol. 1510, p. 477, 1998.

  4. A. A. Freitas and S. H. Lavington
    Parallel Data Mining for Very Large Relational Databases
    Lecture Notes in Computer Science, Vol. 1067, p. 158, 1996.

  5. A. A. Savinov
    Mining Possibilistic Set-Valued Rules by Generating Prime Disjunctions
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 536-541, Springer, September 15-18 1999.

  6. A. An and N. Cercone
    Discretization of Continuous Attributes for Learning Classification Rules
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 509-514, Springer, April 26-28 1999.

  7. A. An and N. Cercone
    Discretization of Continuous Attributes for Learning Classification Rules
    Lecture Notes in Computer Science, Vol. 1574, pp. 509-514, 1999.

  8. A. Feelders
    Handling Missing Data in Trees: Surrogate Splits or Statistical Imputation
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 329-334, Springer, September 15-18 1999.

  9. A. Flewer and H. Bauer
    Discovery of Common Subsequences in Cognitive Evoked Potentials
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 309-317, Springer, September 23-26 1998.

  10. A. G. Ivakhnenko and J. A. Mueller
    Self-Organization of Nets of Active Neurons
    Systems Analysis, Modelling, Simulation (SAMS), 20(2), pp. 93-106, 1995.

  11. A. Imiya and K. Kawamoto
    A Dynamics of the Hough Transform and Artificial Neural Networks
    Proceedings of the 1st International Workshop on Machine Learning and Data Mining in Pattern Recognition (MLDM-99), LNAI, Vol. 1715, pp. 36-50, Springer, September 16-18 1999.

  12. A. Inokuchi and T. Washio and H. Motoda and K. Kumasawa
    Basket Analysis for Graph Structured Data
    Lecture Notes in Computer Science, Vol. 1574, pp. 420-431, 1999.

  13. A. Inokuchi and T. Washio and H. Motoda and K. Kumasawa and N. Arai
    Basket Analysis for Graph Structured Data
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 420-431, Springer, April 26-28 1999.

  14. A. J. Knobbe and A. Siebes and D. van der Wallen
    Multi-relational Decision Tree Induction
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 378-383, Springer, September 15-18 1999.

  15. A. J. Knobbe and H. Blockeel and A. P. J. M. Siebes and D. M. G. van der Wallen
    Multi-Relational Data Mining
    Technical Report, Centrum voor Wiskunde en Informatica, May 1999.

  16. A. Jorge
    Logical Data Mining
    Workshop EKBD-97 associated to EPIA-97, 1997.

  17. A. Maeda and H. Maki and H. Akimori
    Characteristic Rule Induction Algorithm for Data Mining
    Lecture Notes in Computer Science, Vol. 1394, pp. 399-400, 1998.

  18. A. Řhrn and J. Komorowski
    Diagnosing Acute Appendicitis with Very Simple Classification Rules
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 462-467, Springer, September 15-18 1999.

  19. A. P. Sanjeev and J. M. Zytkow
    Modeling the Business Process by Mining Multiple Databases
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 432-440, Springer, September 23-26 1998.

  20. A. R. Pearce and T. Caelli
    The CLARET Algorithm
    Lecture Notes in Computer Science, Vol. 1394, pp. 407-408, 1998.

  21. A. Ragel
    Preprocessing of Missing Values Using Robust Associations Rules
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 414-422, Springer, September 23-26 1998.

  22. A. Ragel and B. Cremilleux
    Treatment of Missing Values for Association Rules
    Lecture Notes in Computer Science, Vol. 1394, pp. 258-270, 1998.

  23. A. Rauber and D. Merkl
    Automatic Labeling of Self-Organizing Maps: Making a Treasure-Map Reveal Its Secrets
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 228-237, Springer, April 26-28 1999.

  24. A. Rauber and D. Merkl
    Automatic Labeling of Self-Organizing Maps: Making a Treasure-Map Reveal Its Secrets
    Lecture Notes in Computer Science, Vol. 1574, pp. 228-237, 1999.

  25. A. Rauber and D. Merkl
    Mining Text Archives: Creating Readable Maps to Structure and Describe Document Collections
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 524-529, Springer, September 15-18 1999.

  26. A. Scaringella
    A Data Mining Application for Monitoring Environmental Risks
    Proceedings of the 1st International Workshop on Machine Learning and Data Mining in Pattern Recognition (MLDM-99), LNAI, Vol. 1715, pp. 209-215, Springer, September 16-18 1999.

  27. A. Siebes
    Data Mining and the KESO Project
    Lecture Notes in Computer Science, Vol. 1175, p. 161, 1996.

  28. A. Skowron and H. S. Nguyen
    Boolean Reasoning Scheme with Some Applications in Data Mining
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 107-115, Springer, September 15-18 1999.

  29. A. Skowron and J. Stepaniuk
    Towards Discovery of Information Granules
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 542-547, Springer, September 15-18 1999.

  30. A. Srinivasan
    A study of two sampling methods for analysing large datasets with ILP
    Data Mining and Knowledge Discovery, 3(1), pp. 95-123, 1999.

  31. A. Srinivasan and R. D. King
    Feature construction with Inductive Logic Programming: a study of quantitative predictions of biological activity aided by structural attributes
    Data Mining and Knowledge Discovery, 3(1), pp. 37-57, 1999.

  32. A. T. Bjorvand
    Object Mining: A Practical Application of Data Mining for the Construction and Maintenance of Software Components
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 121-129, Springer, September 23-26 1998.

  33. A. Zhou and S. Zhou and W. Jin and Z. Tian
    An Improved Definition of Multidimensional Inter-transaction Association Rule,
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 104-108, Springer, April 26-28 1999.

  34. A. Zhou and S. Zhou and W. Jin and Z. Tian
    An Improved Definition of Multidimensional Inter-transaction Association Rule,
    Lecture Notes in Computer Science, Vol. 1574, pp. 104-108, 1999.

  35. A. Zhou and W. Jin and S. Zhou and Z. Tian
    Incremental Mining of Schema for Semi-structured Data
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 159-168, Springer, April 26-28 1999.

  36. A. Zhou and W. Jin and S. Zhou and Z. Tian
    Incremental Mining of Schema for Semi-structured Data
    Lecture Notes in Computer Science, Vol. 1574, pp. 159-168, 1999.

  37. A. Zigbed and M. Cote and N. Troudi
    The Data-Mining and the Technology of Agents to Fight the Illicit Electronic Messages
    Lecture Notes in Computer Science, Vol. 1574, pp. 464-468, 1999.

  38. A. Zighed and M. Côté and N. Troudi
    The Data-Mining and the Technology of Agents to Fight the Illicit Electronic Messages
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 464-468, Springer, April 26-28 1999.

  39. Adriana Gorunescu and Cosmin Dimitriu
    Analyse d'audit
    March 1997.

  40. Alex A. Freitas
    A Genetic Programming Framework for Two Data Mining Tasks: Classification and Generalized Rule Induction
    Genetic Programming 1997: Proceedings of the Second Annual Conference, pp. 96-101, Morgan Kaufmann, 13-16 July 1997.

  41. Alex Alves Freitas
    Scalable, High-Performance Data Mining with Parallel Processing
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 477-477, Springer, September 23-26 1998.

  42. Alexander Hinnenburg and Daniel A. Keim and Markus Wawryniuk
    HD-Eye: Visual Mining of High-Dimensional Data
    IEEE Computer Graphics and Applications, 19(5), pp. 22-31, September 1999.

  43. Alvis Brazma and Jaak Vilo and Esko Ukkonen and Kimmo Valtonen
    Data Mining for Regulatory Elements in Yeast Genome
    Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology, pp. 65-74, AAAI Press, June 21-26 1997.

  44. Andre Colin
    Data-Mining and Genetic Programming
    PC AI, 11(5), p. 23, Knowledge Technology, Inc., Sept/Oct 1997.

  45. Andreas Mueller
    Fast Sequential and Parallel Algorithms for Association Rule Mining: A Comparison
    Technical Report, University of Maryland, College Park, Number CS-TR-3515, August 1995.

  46. Andy N. Pryke
    The Haiku Visualisation System
    Technical Report, School of Computer Science, University of Birmingham, 14 May 1996.

  47. Anne Eisenberg
    Essay: Data mining and privacy invasion on the Net
    Scientific American, 274(3), p. 120, March 1996.

  48. Anonymous
    Lessons in Data Mining
    Byte Magazine, 22(2), p. 40, February 1997.

  49. Anonymous
    MineSet: A System for High-End Data Mining and Visualization
    Proceedings of the twenty-second international Conference on Very Large Data Bases, September 3--6 1996, Mumbai (Bombay), India,, p. 595, Morgan Kaufmann Publishers, 1996.

  50. Anonymous
    Wherefore Warehouse? The future of data mining
    Byte Magazine, 23(1), p. 88NA1, January 1998.

  51. Anthony Tung and Hongjun Lu and Jiawei Han and Ling Feng
    Breaking the Barrier of Transactions: Mining Inter- Transaction Association Rules
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 297-301, ACM Press, August 15-18 1999.

  52. Arno J. Knobbe and Hendrik Blockeel and Arno P. J. M. Siebes and D. M. G. van der Wallen
    Multi-relational data mining
    Technical Report, CWI - Centrum voor Wiskunde en Informatica, Number INS-R9908, May 31, 1999.

  53. Avi Silberschatz and Michael Stonebraker and Jeffrey D. Ullman
    Database Research: Achievements and Opportunities into the 21st Century
    Technical Report, Stanford University, Department of Computer Science, Number CS-TR-96-1563, p. 17, February 1996.

  54. Azer Bestavros
    Discovering Spatial Locality in WWW Access Patterns using Data Mining of Document Clusters in Server Logs
    Technical Report, Boston University, Number 1997-016, August 28, 1997.

  55. Azer Bestavros
    Middleware Support for Data Mining and Knowledge Discovery in Large-scale Distributed Information Systems
    Proceedings of the SIGMOD'96 Data Mining Workshop, June 1996.

  56. B. Back and K. Sere and H. Vanharanta
    Data mining accounting numbers using \mboxself-organizing maps
    STeP '96---Genes, Nets and Symbols. Finnish Artificial Intelligence Conference, pp. 35-47, Univ. Vaasa, 1996.

  57. B. Gray and M. E. Orlowska
    CCAIIA: Clustering Categorical Attributes into Interesting Association Rules
    Lecture Notes in Computer Science, Vol. 1394, pp. 132-143, 1998.

  58. B. Liu and W. Hsu and K. Wang and S. Chen
    Visually Aided Exploration of Interesting Association Rules
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 380-389, Springer, April 26-28 1999.

  59. B. Liu and W. Hsu and K. Wang and S. Chen
    Visually Aided Exploration of Interesting Association Rules
    Lecture Notes in Computer Science, Vol. 1574, pp. 380-389, 1999.

  60. B. Olsson and K. Laurio
    Discovery of Diagnostic Patterns from Protein Sequence Databases
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 167-175, Springer, September 23-26 1998.

  61. B. Zhou and D. W. Cheung and B. Kao
    A Fast Algorithm for Density-Based Clustering in Large Database
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 338-349, Springer, April 26-28 1999.

  62. B. Zhou and D. W. Cheung and B. Kao
    A Fast Algorithm for Density-Based Clustering in Large Database
    Lecture Notes in Computer Science, Vol. 1574, pp. 338-349, 1999.

  63. B.-Y. Sher and S.-C. Shao and W.-S. Hsieh
    Mining Regression Rules and Regression Trees
    Lecture Notes in Computer Science, Vol. 1394, pp. 271-282, 1998.

  64. Barbara Eckman and Jeffrey S. Aaronson and Joseph A. Borkowski and Wendy J. Bailey and Keith O. Elliston and Alan R. Williamson and Richard A. Blevins
    The Merck Gene Index Browser: an extensible data integration system for gene finding, gene characterization and EST data mining
    Bioinformatics, 14(1), pp. 2-13, 1998.

  65. Béla Bollobás and Gautam Das and Dimitrios Gunopulos and Heikki Mannila
    Time-Series Similarity Problems and Well-Separated Geometric Sets
    Proc. 13th ACM Symp. Computational Geometry, SCG, pp. 454-456, ACM Press, 4-6 June 1997.

  66. Bin Li and Dennis Shasha
    Free Parallel Data Mining
    Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD-98), ACM SIGMOD Record, Vol. 27,2, pp. 541-543, ACM Press, June 1-4 1998.

  67. Bin Li and Dennis Shasha
    Free Parallel Data Mining
    SIGMOD Record (ACM Special Interest Group on Management of Data), 27(2), p. 541, 1998.

  68. Bing Liu and Wynne Hsu and Ke Wang and Shu Chen
    Visually Aided Exploration of Interesting Association Rules
    Research and Development in Knowledge Discovery and Data Mining: Proceedings of the 3rd Pacific-Asia Conferences on Knowledge Discovery and Data Mining, Lecture Notes in Artificial Intelligence, Springer, 1999.

  69. Bing Liu and Wynne Hsu and Yiming Ma
    Mining Association Rules with Multiple Minimum Supports
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 337-341, ACM Press, August 15-18 1999.

  70. Bing Liu and Wynne Hsu and Yiming Ma
    Pruning and Summarizing the Discovered Associations
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 125-134, ACM Press, August 15-18 1999.

  71. Bing Liu and Wynne Jsu and Yiming Ma and Shu Chen
    Mining Interesting Knowledge Using DM-II
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 430-434, ACM Press, August 15-18 1999.

  72. Biswadeep Nag and Prasad Deshpande and David J. DeWitt
    Using a Knowledge Cache for Interactive Discovery of Association Rules
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 244-253, ACM Press, August 15-18 1999.

  73. Bjrnar Larsen and Chinatsu Aone
    Fast and Effective Text Mining Using Linear-time Document Clustering
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 16-22, ACM Press, August 15-18 1999.

  74. Brian Lent and Rakesh Agrawal and Ramakrishnan Srikant
    Discovering Trends in Text Databases
    Proc. 3rd Int. Conf. Knowledge Discovery and Data Mining, KDD, pp. 227-230, AAAI Press, 14-17 August 1997.

  75. C. Anglano and A. Giordana and G. Lo Bello
    High-performance data mining on networks of workstations
    Proceedings of the 11th International Symposium on Foundations of Intelligent Systems (ISMIS-99), LNAI, Vol. 1609, pp. 520-528, Springer, June 08-11 1999.

  76. C. Anglano and A. Giordana and G. Lo Bello
    High-performance data mining on networks of workstations
    Lecture Notes in Computer Science, Vol. 1609, p. 520, 1999.

  77. C. C. Aggarwal and P. S. Yu
    Data Mining Techniques for Associations, Clustering and Classification
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 13-23, Springer, April 26-28 1999.

  78. C. C. Aggarwal and P. S. Yu
    Data Mining Techniques for Associations, Clustering and Classification
    Lecture Notes in Computer Science, Vol. 1574, pp. 13-23, 1999.

  79. C. Clifton and R. Cooley
    TopCat:Data Mining for Topic Identification in a Text Corpus
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 174-183, Springer, September 15-18 1999.

  80. C. Deng and F. Xiong
    Neural Method for Detection of Complex Patterns in Databases
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 258-262, Springer, April 26-28 1999.

  81. C. Deng and F. Xiong
    Neural Method for Detection of Complex Patterns in Databases
    Lecture Notes in Computer Science, Vol. 1574, pp. 258-262, 1999.

  82. C. Guerra-Salcedo and D. Whitley
    Feature selection mechanisms for ensemble creation: a genetic search perspective
    Data Mining with Evolutionary Algorithms: Research Directions, pp. 13-17, AAAI Press, 18 July 1999.

  83. C. H. Bryant
    Data Mining via ILP: The Application of Progol to a Database of Enantioseparations
    Lecture Notes in Computer Science, Vol. 1297, p. 85, 1997.

  84. C. H. Papadimitriou
    Algorithmic Approaches to Information Retrieval and Data Mining
    Lecture Notes in Computer Science, Vol. 1449, p. 1, 1998.

  85. C. H. Papadimitriou
    Novel Computational Approaches to Information Retrieval and Data Mining p. 31
    Lecture Notes in Computer Science, Vol. 1540, p. 31, 1999.

  86. C. J. Kennedy and C. Giraud-Carrier and D. W. Bristol
    Predicting Chemical Carcinogenesis Using Structural Information Only
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 360-365, Springer, September 15-18 1999.

  87. C. L. Tsien and S. M. Hamish and S. F. Fraser and I. S. Kohane
    LR Tree: A Hybrid Technique for Classifying Myocardial Infarction Data Containing Unknown Attribute Values
    Lecture Notes in Computer Science, Vol. 1394, pp. 409-411, 1998.

  88. C. L. Yip and K. K. Loo and B. Kao and D. W. Cheung
    LGen --- A Lattice-Based Candidate Set Generation Algorithm for I/O Efficient Association Rule Mining
    Lecture Notes in Computer Science, Vol. 1574, pp. 54-63, 1999.

  89. C. L. Yip and K. K. Loo and B. Kao and D. W. Cheung and C. K. Cheng
    LGen - A Lattice-Based Candidate Set Generation Algorithm for I/O Efficient Association Rule Mining
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 54-63, Springer, April 26-28 1999.

  90. C. M. De Oca and D. L. Carver
    Design Recovery with Data Mining Techniques
    Lecture Notes in Computer Science, Vol. 1394, pp. 405-406, 1998.

  91. C. Marsala
    Application of Fuzzy Rule Induction to Data Mining
    Lecture Notes in Computer Science, Vol. 1495, p. 260, 1998.

  92. C. Nowak
    Multiple Databases, Partial Reasoning, and Knowledge Discovery
    Lecture Notes in Computer Science, Vol. 1394, pp. 403-404, 1998.

  93. C. P. Rainsford and J. F. Roddick
    Adding Temporal Semantics to Association Rules
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 504-509, Springer, September 15-18 1999.

  94. C. Pizzuti and D. Talia and G. Vonella
    A Divisive Initialization Method for Clustering Algorithms
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 484-491, Springer, September 15-18 1999.

  95. C. S. Fertig and A. A. Freitas and L. V. R. Arruda and C. Kaestner
    A Fuzzy Beam-Search Rule Induction Algorithm
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 341-347, Springer, September 15-18 1999.

  96. C. Stumme and R. Wille and U. Wille
    Conceptual Knowledge Discovery in Databases Using Formal Concept Analysis Methods
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 450-458, Springer, September 23-26 1998.

  97. C.-H. Chang and C.-C. Hsu
    Constructing Personalized Information Agents
    Lecture Notes in Computer Science, Vol. 1394, pp. 374-375, 1998.

  98. C.-J. Liau and D.-R. Liu
    A Logical Approach to Fuzzy Data Analysis
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 412-417, Springer, September 15-18 1999.

  99. C.-M. Su and S.-S. Tseng and M.-F. Jiang and J. C. S. Chen
    A Fast Clustering Process for Outliers and Remainder Clusters
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 360-364, Springer, April 26-28 1999.

  100. C.-M. Su and S.-S. Tseng and M.-F. Jiang and J. C. S. Chen
    A Fast Clustering Process for Outliers and Remainder Clusters
    Lecture Notes in Computer Science, Vol. 1574, pp. 360-364, 1999.

  101. Carlos Montes de Oca and Doris L Carver
    A Visual Representation Model for Software Subsystem Decomposition
    Working Conference on Reverse Engineering, pp. 231-240, IEEE Computer Society Press, October 1998.

  102. Carsten Jacobsen and Uwe Zscherpel and Petra Perner
    A Comparison between Neural Networks and Decision Trees
    Proc. 1st Int. Work. Machine Learning and Data Mining in Pattern Recognition, MLDM, Lecture Notes in Artificial Intelligence, LNAI, Number 1715, Springer-Verlag, September 1999.

  103. Catherine Plaisant and Gary Marchionini and Tom Bruns and Anita Komlodi and Laura Campbell
    Bringing Treasures to the Surface: Iterative Design for the Library of Congress National Digital Library Program
    Proceedings of ACM CHI 97 Conference on Human Factors in Computing Systems, DESIGN BRIEFINGS: Access to Knowledge: Libraries and Data Mining, Vol. 1, pp. 518-525, 1997.

  104. Ceil Chua Eng Huang and R. H. L. Chiang and E.-P. Lim
    A Heuristic Method for Correlating Attribute Group Pairs in Data Mining
    Lecture Notes in Computer Science, Vol. 1552, pp. 29-40, 1999.

  105. Charu Aggarwal and Joel Wolf and Kun-Lung Wu and Philip Yu
    Horting Hatches an Egg: A New Graph-Theoretic Approach to Collaborative Filtering
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 201-212, ACM Press, August 15-18 1999.

  106. Charu Aggarwal and Stephen Gates and Philip Yu
    On the Merits of Bilding Categorization Systems by Supervised Clustering
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 352-356, ACM Press, August 15-18 1999.

  107. Charu C. Aggarwal and Stephen C. Gates and Philip S. Yu
    On the merits of building categorization systems by supervised clustering
    Proceedings of SIGKDD-99, 5th ACM International Conference on Knowledge Discovery and Data Mining, pp. 352-356, ACM Press, New York, US, 1999.

  108. Chen
    Hedging Derivative Securities with Genetic Programming
    Application of Machine Learning and Data Mining in Finance: Workshop at ECML-98, 24 April 1998.

  109. Chia-Hui Chang and Ching-Chi Hsu
    Constructing Personalized Information Agents
    Research and Development in Knowledge Discovery and Data Mining, Proc. 2nd Pacific-Asia Conf. Knowledge Discovery and Data Mining, PAKDD, Lecture Notes in Artificial Intelligence, LNAI, Vol. 1394, pp. 374-375, Springer, 15-17 April 1998.

  110. Chidanand Apté
    CSE in Industry: Data Mining: An Industrial Research Perspective
    IEEE Computational Science & Engineering, 4(2), pp. 6-9, April /jun 1997.

  111. Chidanand Apté and Sholom M. Weiss
    Data mining with decision trees and decision rules
    Future Generation Computer Systems, Vol. 13, pp. 197-210, 1997.

  112. Chris P. Rainsford and John F. Roddick
    A Survey of Issues in Data Mining
    Technical Report, School of Computer and Information Science, University of South Australia, Number CIS-96-006, July 1996.

  113. Christian Setzkorn
    Investigation into the Application of Artificial Intelligence Methods to the Analysis of Medical Data
    Technical Report, Computer Science Department, University of Liverpool, January 2000.

  114. Christophe Giraud-Carrier and Stephen Corley
    Inductive CBR for Customer Support
    Proceedings of the Second International Conference on the Practical Application of Knowledge Discovery and Data Mining, pp. 131-141, The Practical Application Company Ltd, March 1998.

  115. Christopher G. Healey
    On the Use of Perceptual Cues and Data Mining for Effective Visualization of Scientific Datasets
    Proceedings of the 24th Conference on Graphics Interface (GI-98), pp. 177-184, Morgan Kaufmann Publishers, June 18-20 1998.

  116. Christopher G. Healey
    On the Use of Perceptual Cues and Data Mining for Effective Visualization of Scientific Datasets
    Graphics Interface, pp. 177-184, June 1998.

  117. Christopher H. Bryant
    Data Mining via ILP: The Application of Progol to a Database of Enantioseparations
    Proceedings of the 7th International Workshop on Inductive Logic Programming, LNAI, Vol. 1297, pp. 85-92, Springer, September 17-20 1997.

  118. Chun-hung Cheng and Ada Wai-chee Fu and Yi Zhang
    Entropy- based Subspace Clustering for Mining Numerical Data
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 84-93, ACM Press, August 15-18 1999.

  119. Corinna Cortes and Daryl Pregibon
    Information Mining Platforms: An infrastructure for KDD rapid deployment
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  125. D. A. Newlands and G. I. Webb
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  127. D. Landau and R. Feldman and O. Zamir and Y. Aumann and M. Fresko and Y. Lindell and O. Lipshtat
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  128. D. Li and K. Di and D. Li and X. Shi
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  129. D. McSherry
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  131. D. R. Mani and James Drew and Andrew Betz and Piew Datta
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    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 94-103, ACM Press, August 15-18 1999.

  132. D. Shibata and N. Inuzuka and S. Kato and T. Matsui
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  133. D. Shibata and N. Inuzuka and S. Kato and T. Matsui and H. Itoh
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  134. D. W. Albrecht and A. E. Nicholson and I. Zukerman
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  135. D. W. Cheung and Y. Xiao
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  136. D. Walker and O. Rana
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  137. D. Watkins
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  138. D. Yu and A. Zhang
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  139. D. Zelenko
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  140. Daisuke Shibata and Nobuhiro Inuzuka and Shohei Kato and Tohgoroh Matsui and Hidenori Itoh
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  141. Damianos Chatziantoniou
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  142. Dan Pelleg and Andrew Moore
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  143. Daniel A. Keim and Hans-Peter Kriegel and Thomas Seidl
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  144. Daniel Barbara and Xintao Wu
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  145. Daniel Keim
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  146. Daryl Pregibon
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  147. Database Mining and Visualisation Group---SGI Inc.
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  148. David Cooke and Carlos Ordonez and Ernie Garcia and Edward Omiecinski and Elyzabeth Krawczynska and R. Folks and C. Santana and Levien de Braal and Norberto Ezquerra
    Data Mining of Large Myocardial Perfusion SPECT (MPS) Databases to Improve Diagnostic Decision Making
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  149. David D. Lewis and Daniel L. Stern and Amit Singhal
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  150. David Heckerman and Heikki Mannila and Daryl Pregibon and Ramasamy Uthurusamy (eds.)
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  151. David J. Hand
    Data Mining: Statistics and More?
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  152. David L. Dowe and Lloyd Allison and Glen Pringle
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  153. Deborah Swayne and Diane Cook
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  154. D-I Lin and Z. Kedem
    Pincer-Search: A New Algorithm for Discovering the Maximum Frequent Set
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  155. Dimitrios Gunopulos and Heikki Mannila and Roni Khardon and Hannu Toivonen
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    PODS '97. Proceedings of the Sixteenth ACM SIG-SIGMOD-SIGART Symposium on Principles of Database Systems, May 12--14, 1997, Tucson, Arizona, pp. 209-216, ACM Press, 1997.

  156. Dimitrios Gunopulos and Roni Khardon and Heikki Mannila and Hannu Toivonen
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  157. Dimitris Meretakis and Beat Wüthrich
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  158. É. Alphonse and C. Rouveirol
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  159. E. Bertino and B. Catania and E. Caglio
    Applying Data Mining Techniques to Wafer Manufacturing
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  160. E. Collopy and M. Levene
    Resampling in an Indefinite Database to Approximate Functional Dependencies
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  161. E. Hotz and G. Nakhaeizadeh and B. Petzsche and H. Spiegelberger
    WAPS, a Data Mining Support Environment For The Planning Of Warranty And Goodwill Costs In The Automobile Industry
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 417-419, ACM Press, August 15-18 1999.

  162. E. J. Keogh and M. J. Pazzani
    Scaling up Dynamic Time Warping to Massive Dataset
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  163. E. J. Son and I. S. Kang and T. W. Kim and K. J. Li
    A Spatial Data Mining Method by Clustering Analysis
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  164. E. Mayoraz and M. Moreira
    Combinatorial Approach for Data Binarization
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  165. E. Suzuki and T. Ohno
    Prediction Rule Discovery Based on Dynamic Bias Selection
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  166. E. Suzuki and T. Ohno
    Prediction Rule Discovery Based on Dynamic Bias Selection
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  167. E. Suzuki and Y. Kodratoff
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    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 10-18, Springer, September 23-26 1998.

  168. Edgar Noda and Alex A. Freitas and Heitor S. Lopes
    Discovering Interesting Prediction Rules with a Genetic Algorithm
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  169. Edmund X. Dejesus
    Data Mining --- There's gold in those hills of data
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  170. Ellen Spertus
    ParaSite: Mining Structural Information on the Web
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  171. Endre Boros and Takashi Horiyama and Toshihide Ibaraki and Kazuhisa Makino and Mutsunori Yagiura
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  172. Eric Bloedorn and Ryszard S. Michalski
    Data-Driven Constructive Induction
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  173. Erik Riedel and Garth A. Gibson and Christos Faloutsos
    Active Storage for Large-Scale Data Mining and Multimedia
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  174. Eui-Hong Han and George Karypis and Vipin Kumar
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  175. Eui-Hong Han and George Karypis and Vipin Kumar
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  176. Evangelos Kranakis and Danny Krizanc and Andrzej Pelc and David Peleg
    The Complexity of Data Mining on the Web
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  177. Evangelos Kranakis and Danny Krizanc and Andrzej Pelc and David Peleg
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  178. F. Bonchi and F. Giannotti and G. Mainetto and D. Pedreschi
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  179. F. Coenen and G. Swinnen and K. Vanhoof and G. Wets
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  182. F. Masseglia and F. Cathala and P. Poncelet
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  183. F. Murtagh (ed.)
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  184. Fabbrocino Frank and Shek Eddie and Muntz Richard
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  185. Fagiuoli E. and Zaffalon M.
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  186. Felicity George
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  187. Flip Korn and Alexandros Labrinidis and Yannis Kotidis and Christos Faloutsos
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  188. Flip Korn and Alexandros Labrinidis and Yannis Kotidis and Christos Faloutsos and Alex Kaplunovich and Dejan Perkovic
    Quantifiable Data Mining Using Principal Component Analysis
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  189. Foster Provost and David Jensen and Tim Oates
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  190. Fran\c cois Jacquenet and Patrice Brenot
    Learning User Preferences on the WEB
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  191. Friedrich Gebhardt
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  192. Fukuda and Morimoto and Morishita and Tokuyama
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  193. G. Deboeck
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  195. G. Giacinto and F. Roli
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  200. G. M. Weiss
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  202. G. Melli
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  203. G. Melli
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  204. G. Nakhaeizadeh
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  205. G. Paass and J. Kindermann
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  206. G. Piatetsky-Shapiro
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  208. G. Piatetsky-Shapiro
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  210. G. Venturini and M. Slimane and F. Morin and J.-P. Asselin de Beauville
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  212. Gediminas Adomavicius and Alexander Tuzhilin
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  213. George H. John and Pat Langley
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  214. Gerald Fahner
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  215. Gerard Jorna and Mirjam Wouters and Paul Gardien and Hans Kemp and Jack Mama and Irene Mavromati and Ian McClelland and Linda Vodegel Matzen
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  216. Gholamreza Nakhaeizadeh
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  217. Gianluigi Folino and Clara Pizzuti and Giandomenico Spezzano
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  219. Gregory Piatetsky-Shapiro and Brij Masand
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  220. Gunjan Jha and Siu Cheung Hui
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  221. Guozhu Dong and Jinyan Li
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  222. Guozhu Dong and Jinyan Li
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  223. Gusz Eiben
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  224. H. A. Abbass and P. Macrossan and M. Towsey and K. Mengersen and G. D. Finn
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  225. H. A. Prado and K. F. Machado and S. R. Frigeri and P. M. Engel
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  226. H. A. Prado and K. F. Machado and S. R. Frigeri and P. M. Engel
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  227. H. Blockeel and S. Dzeroski and J. Grbovi\'c
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  228. H. Brighton and C. Mellish
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  230. H. Dai
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  231. H. Dai
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  232. H. He and S. Hawkins
    Optimising the Distance Metric in the Nearest Neighbour Algorithm on a Real-World Patient Classification Problem
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  235. H. J. Hamilton and R. J. Hilderman and L. Li and D. J. Randall
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  236. H. Jahn
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  352. K. M. Ting
    Inducing Cost-Sensitive Trees via Instance Weighting
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 139-147, Springer, September 23-26 1998.

  353. K. M. Ting and Z. Zheng
    Improving the Performance of Boosting for Naive Bayesian Classification
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 296-305, Springer, April 26-28 1999.

  354. K. M. Ting and Z. Zheng
    Improving the Performance of Boosting for Naive Bayesian Classification
    Lecture Notes in Computer Science, Vol. 1574, pp. 296-305, 1999.

  355. K. Matsumoto
    Exploratory Attributes Search in Times-Series Data: An Experimental System for Agricultural Application
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 388-395, Springer, September 23-26 1998.

  356. K. Rajamani and S. Sung and A. Cox
    Extending the Applicability of Association Rules
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 64-73, Springer, April 26-28 1999.

  357. K. Rajamani and S. Sung and A. Cox
    Extending the Applicability of Association Rules
    Lecture Notes in Computer Science, Vol. 1574, pp. 64-73, 1999.

  358. K.-C. Lee
    A Technique of Dynamic Feature Selection Using the Feature Group Mutual Information
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 138-142, Springer, April 26-28 1999.

  359. K.-C. Lee
    A Technique of Dynamic Feature Selection Using the Feature Group Mutual Information
    Lecture Notes in Computer Science, Vol. 1574, pp. 138-142, 1999.

  360. Kan Chen and Huan Liu
    Digital Circuit Evolution and Fitness Landscapes 1299 Vesselin K. Vassilev Julian F. Miller Terence C. Fogarty Towards an Evolutionary Algorithm: A Comparison of Two Feature Selection Algorithms
    Proceedings of the Congress on Evolutionary Computation, Vol. 2, pp. 1309-1313, IEEE Press, 6-9 July 1999.

  361. Kaula
    review of Adriaans & Zantinge, Data Mining (Addison-Wesley, 1997)
    COMPREVS: ACM Computing Reviews, Vol. 38, 1997.

  362. Kazunori Matsumoto
    An Experimental Agricultural Data Mining System
    Proceedings of the 1st International Conference on Discovery Science (DS-98), LNAI, Vol. 1532, pp. 439-440, Springer, December 14-16 1998.

  363. Kazunori Matsumoto and Takeo Hayase and Nobuyuki Ikeda
    Data Mining of Generalized Association Rules Using a Method of Partial-Match Retrieval
    Proceedings of the 2nd International Conference on Discovery Science (DS-99), LNAI, Vol. 1721, pp. 160-171, Springer, December 6-8 1999.

  364. Ke Wang and Huiqing Liu
    Schema Discovery for Semistructured Data
    Third International Conference on Knowledge Discovery and Data Mining (KDD-97), pp. 271-274, 1997.

  365. Kenji Satou and Toshihide Ono and Yoshihisa Yamamura and Emiko Furuichi and Satoru Kuhara and Toshihisa Takagi
    Extraction of Substructures of Proteins Essential to their Biological Functions by a Data Mining Technique
    Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology, pp. 254-257, AAAI Press, June 21-26 1997.

  366. Kenneth C. Cox and Stephen G. Eick and Graham J. Wills and Ronald J. Brachman
    Visual Data Mining: Recognizing Telephone Calling Fraud
    J. Data Mining and Knowledge Discovery, 1(2), pp. 225-231, Kluwer Academic Publishers, 1997.

  367. KianSing Ng and Huan Liu and HweeBong Kwah
    A Data Mining Application: Customer Retention at the Port of Singapore Authority (PSA)
    SIGMOD Record (ACM Special Interest Group on Management of Data), 27(2), p. 522, 1998.

  368. KianSing Ng and Huan Liu and HweeBong Kwah
    A Data Mining Application: Customer Retention at the Port of Singapore Authority (PSA)
    Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD-98), ACM SIGMOD Record, Vol. 27,2, pp. 522-525, ACM Press, June 1-4 1998.

  369. Krista Lagus and Timo Honkela and Samuel Kaski and Teuvo Kohonen
    Self-organizing maps of document collections: A new approach to interactive exploration
    Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, pp. 238-243, AAAI Press, 1996.

  370. Kristin Bennett and Usama Fayyad and Dan Geiger
    Density-Based Indexing for Approximate Nearest-Neighbor Queries
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,