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. Øhrn 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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    Technical Report, University of Rochester, Computer Science Department, Number TR617, May 1996.

  471. N. Dewhurst and S. Lavington
    Knowledge Discovery from Client-Server Databases
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 300-308, Springer, September 23-26 1998.

  472. N. J. Radcliffe and P. D. Surry
    Cooperation through Hierarchical Competition in Genetic Data Mining
    Technical Report, Parallel Computing Centre, University of Edinburgh, Number EPCC-TR94-09, 1994.

  473. N. Lavrac
    Machine Learning for Data Mining in Medicine
    Lecture Notes in Computer Science, Vol. 1620, p. 47, 1999.

  474. N. Lavrac
    Machine Learning for Data Mining in Medicine
    Proceedings of the Joint European Conference on Artificial Intellingence in Medicine and Medical Decision Making (AIMDM-99), LNAI, Vol. 1620, pp. 47-64, Springer, June 20-24 1999.

  475. N. M. Bigolin and C. Marsala
    Fuzzy Spacial OQL for Fuzzy Knowledge Discovery in Databases
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 246-254, Springer, September 23-26 1998.

  476. N. M. Marques and C. P. Lopes and C. A. Coelho
    Using Loglinear Clustering for Subcategorization Identification
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 379-387, Springer, September 23-26 1998.

  477. N. Monmarche
    On data clustering with artificial ants
    Data Mining with Evolutionary Algorithms: Research Directions, pp. 23-26, AAAI Press, 18 July 1999.

  478. N. Nikolaev and H. Iba
    Automated Discovery of Polynomials by Inductive Genetic Programming
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 456-461, Springer, September 15-18 1999.

  479. N. Xiong and L. Litz
    Generating Linguistic Fuzzy Rules for Pattern Classification with Genetic Algorithms
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 574-579, Springer, September 15-18 1999.

  480. N. Zhong and C. Liu and Y. Kakemoto and S. Ohsuga
    Handling KDD Process Changes by Incremental Replanning
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 111-120, Springer, September 23-26 1998.

  481. N. Zhong and J. Dong and S. Ohsuga
    Data Mining Based on the Generalization Distribution Table and Rough Sets
    Lecture Notes in Computer Science, Vol. 1394, pp. 360-373, 1998.

  482. N. Zhong and J. Dong and S. Ohsuga
    Soft techniques to data mining
    Lecture Notes in Computer Science, Vol. 1424, p. 231, 1998.

  483. N. Zhong and J. Dong and S. Ohsuga
    Soft techniques to data mining
    Proceedings of the 1st International Conference on Rough Sets and Current Trends in Computing (RSCTC-98), LNAI, Vol. 1424, pp. 231-238, Springer, June 22-26 1998.

  484. N. Zhong and Y. Y. Yao and S. Ohsuga
    Peculiarity Oriented Multi-database Mining
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 136-146, Springer, September 15-18 1999.

  485. Nadeem Ahmed Syed and Huan Liu and Kah Kay Sung
    A Study of Support Vectors on Model Independent Example Selection
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 272-276, ACM Press, August 15-18 1999.

  486. Nadeem Ahmed Syed and Huan Liu and Kah Kay Sung
    Handling Concept Drifts in Incremental Learning with Support Vector Machines
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 317-321, ACM Press, August 15-18 1999.

  487. Neal Lesh and Mohammed J. Zaki and Mitsunori Ogihara
    Mining Features for Sequence Classification
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 342-346, ACM Press, August 15-18 1999.

  488. Necip Fazil Ayan and Abdullah Uz Tansel and Erol Arkun
    An Efficient Algorithm to Update Large Itemsets with Early Pruning
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 287-291, ACM Press, August 15-18 1999.

  489. Nicholas J. Radcliffe and Patrick D. Surry
    Co-operation through Hierarchical Competition in Genetic Data Mining
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  490. Ning Zhong and Lizhu Zhou (eds.)
    Methodologies for knowledge discovery and data mining: Third Pacific-Asia Conference, PAKDD-99, Beijing China, April 26--28, 1999: proceedings,
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  491. Ning Zhong and Lizhu Zhou (eds.)
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99)
    , LNAI, Vol. 1574, Springer, April 26-28 1999.

  492. O. Altamura and F. Esposito and F. A. Lisi and D. Malerba
    Symbolic Learning Techniques in Paper Document Processing
    Proceedings of the 1st International Workshop on Machine Learning and Data Mining in Pattern Recognition (MLDM-99), LNAI, Vol. 1715, pp. 159-173, Springer, September 16-18 1999.

  493. O. Buechter and R. Wirth
    Discovery of Association Rules over Ordinal Data: A New and Faster Algorithm and Its Application to Basket Analysis
    Lecture Notes in Computer Science, Vol. 1394, pp. 36-47, 1998.

  494. O. De Vel and D. Coomans and S. Patrick
    Feature Mining and Mapping of Collinear Data
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  495. O. L. Mangasarian
    Mathematical Programming in Data Mining
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  496. O. O. Lobo and M. Numao
    Ordered Estimation of Missing Values
    Lecture Notes in Computer Science, Vol. 1574, pp. 499-503, 1999.

  497. O. O. Lobo and M. Numao
    Ordered Estimation of Missing Values
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 499-503, Springer, April 26-28 1999.

  498. Osmar R. Zaiane
    From Resource Discovery to Knowledge Discovery on the Internet
    Technical Report, School of Computing Science, Simon Fraser University Burnaby, BC, Canada,, Number TR 1998-13, p. 65, August 1998.

  499. Osmar R. Zaiane and Jiawei Han and Ze-Nian Li and Sonny H. Chee and Jenny Y. Chiang
    MultiMediaMiner: A System Prototype for MultiMedia Data Mining
    SIGMOD Record (ACM Special Interest Group on Management of Data), 27(2), p. 581, 1998.

  500. Osmar R. Zaiane and Jiawei Han and Ze-Nian Li and Sonny H. Chee and Jenny Y. Chiang
    MultiMediaMiner: A System Prototype for MultiMedia Data Mining
    Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD-98), ACM SIGMOD Record, Vol. 27,2, pp. 581-583, ACM Press, June 1-4 1998.

  501. Osmar R. Zaïane and Man Xin and Jiawei Han
    Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web Logs
    Proc. Advances in Digital Libraries, ADL, pp. 19-29, April 1998.

  502. P. A. Flach
    From extensional to intensional knowledge: Inductive Logic Programming techniques and their application to deductive databases
    Transactions and Change in Logic Databases, Lecture Notes in Computer Science, Vol. 1472, pp. 356-387, Springer-Verlag, 1998.

  503. P. Berka and I. Bruha
    Discretization and Grouping: Preprocessing Steps for Data Mining
    Lecture Notes in Computer Science, Vol. 1510, p. 239, 1998.

  504. P. Berka and I. Bruha
    Discretization and Grouping: Preprocessing Steps for Data Mining
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 239-245, Springer, September 23-26 1998.

  505. P. Bosc and L. Liétard and O. Pivert
    Extended Functional Dependencies as a Basis for Linguistic Summaries
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 255-263, Springer, September 23-26 1998.

  506. P. Cago and C. Bento
    A Metric for Selection of the Most Promising Rules
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 19-27, Springer, September 23-26 1998.

  507. P. Cheeseman and J. Stutz
    Bayesian classification (AUTOCLASS): Theory and results
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  508. P. D. Scott and A. P. M. Coxon and M. H. Hobbs and R. J. Williams
    An intelligent assistant for exploratory data analysis
    Proceedings First European Symposium on Principles of Data Mining & Knowledge Discovery, p. 11pp, Springer Verlag, January 1997.

  509. P. D. Scott and R. J. Williams and K. M. Ho
    Forming Categories in Exploratory Data Analysis and Data Mining
    Lecture Notes in Computer Science, Vol. 1280, p. 235, 1997.

  510. P. Datta
    Business Focused Evaluation Methods: A Case Study
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 316-322, Springer, September 15-18 1999.

  511. P. Hájek and J. Rauch
    Logics and Statistics for Association Rules and Beyond
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 586-587, Springer, September 15-18 1999.

  512. P. Hunziker and A. Maier and A. Nippe and M. Tresch
    Data Mining at a Major Bank: Lessons from a Large Marketing Application
    Lecture Notes in Computer Science, Vol. 1510, p. 345, 1998.

  513. P. Hunziker and A. Maier and A. Nippe and M. Tresch and D. Weers and P. Zemp
    Data Mining at a Major Bank: Lessons from a Large Marketing Application
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 345-351, Springer, September 23-26 1998.

  514. P. Perrin and F. Petry
    Contextual Text Representation for Unsupervised Knowledge Discovery in Texts
    Lecture Notes in Computer Science, Vol. 1394, pp. 246-257, 1998.

  515. P. S. Bradley and U. M. Fayyad and O. L. Mangasarian
    Mathematical programming for data mining: formulations and challenges
    INFORMS Journal on Computing, Vol. 11(3), pp. 217-238, 1999.

  516. P. S. M. Tsai and C.-C. Lee and A. L. P. Chen
    An Efficient Approach for Incremental Association Rule Mining
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 74-83, Springer, April 26-28 1999.

  517. P. S. M. Tsai and C.-C. Lee and A. L. P. Chen
    An Efficient Approach for Incremental Association Rule Mining
    Lecture Notes in Computer Science, Vol. 1574, pp. 74-83, 1999.

  518. Pak Chung Wong
    Visual Data Mining
    IEEE Computer Graphics and Applications, 19(5), pp. 20-21, September 1999.

  519. Papadimitriou
    Algorithmic Approaches to Information Retrieval and Data Mining (one page only)
    COCOON: Annual International Conference on Computing and Combinatorics, 1998.

  520. Papadimitriou
    Novel Computational Approaches to Information Retrieval and Data Mining (one page only)
    ICDT: 7th International Conference on Database Theory, 1999.

  521. Patrick Flanagan
    10 hottest technologies in telecom
    Telecommunications (Americas Edition), 30(5), May 1996.

  522. Patrick Hoffman and Georges Grinstein and Kenneth Marx and Ivo Grosse and Eugene Stanley
    DNA Visual And Analytic Data Mining
    IEEE Visualization \'97, pp. 437-442, November 1997.

  523. Patrick Hoffman and Georges Grinstein and Kenneth Marx and Ivo Grosse and Eugene Stanley
    DNA Visual And Analytic Data Mining (Color Plate S. 572)
    Proceedings of the 8th Annual IEEE Conference on Visualization (VISU-97), pp. 437-442, IEEE Computer Society Press, October 19-24 1997.

  524. Patrick Perrin and Fred Petry
    Contextual Text Representation for Unsupervised Knowledge Discovery in Texts
    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. 246-257, Springer, 15-17 April 1998.

  525. Patrick Tufts
    Parallel Case Evaluation for Genetic Programming
    1993 Lectures in Complex Systems, Santa Fe Institute Studies in the Science of Complexity, Vol. VI, pp. 591-596, Addison-Wesley, 1995.

  526. Pedro Domingos
    MetaCost:A General Method for Making Classifiers Cost-Sensitive
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 155-164, ACM Press, August 15-18 1999.

  527. Peter Flach
    From extensional to intensional knowledge: Inductive Logic Programming techniques and their application to deductive databases
    Transactions and Change in Logic Databases, Vol. LNCS 1472, pp. 356-387, Springer-Verlag, December 1998.

  528. Petra Perner and Maria Petrou (eds.)
    Proceedings of the 1st International Workshop on Machine Learning and Data Mining in Pattern Recognition (MLDM-99)
    , LNAI, Vol. 1715, Springer, September 16-18 1999.

  529. Philip G. K. Reiser and Patricia J. Riddle
    Evolution of Logic Programs: Part-of-Speech Tagging
    Proceedings of the Congress on Evolutionary Computation, Vol. 2, pp. 1338-1346, IEEE Press, 6-9 July 1999.

  530. R. Cattral and F. Oppacher and D. Deugo
    Using Genetic Algorithms to Evolve a Rule Hierarchy
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 289-294, Springer, September 15-18 1999.

  531. R. Cole and P. Eklund
    Analyzing an Email Collection Using Formal Concept Analysis
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 309-315, Springer, September 15-18 1999.

  532. R. Cole and P. Eklund and D. Walker
    Constructing Conceptual Scales in Formal Concept Analysis
    Lecture Notes in Computer Science, Vol. 1394, pp. 378-379, 1998.

  533. R. Englert
    Acquisition of Complex Model Knowledge by Domain Theory-Controlled Generalization
    Computing, 62(4), pp. 369-385, 1999.

  534. R. Feldman and M. Fresko and Y. Kinar and Y. Lindell and O. Lipshtat and M. Rajman and Y. Schler and O. Zamir
    Text Mining at the Term Level
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 65-73, Springer, September 23-26 1998.

  535. R. Feldman and Y. Aumann and A. Zilberstein and Y. Ben-Yehuda
    Trend Graphs: Visualizing the Evolution of Concept Relationships in Large Document Collections
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 38-46, Springer, September 23-26 1998.

  536. R. Feldman and Y. Aumann and M. Fresko and O. Liphstat and B. Rosenfeld and Y. Schler
    Text Mining via Information Extraction
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 165-173, Springer, September 15-18 1999.

  537. R. J. Hilderman and C. L. Carter and H. J. Hamilton and N. Cercone
    Mining Market Basket Data Using Share Measures and Characterized Itemsets
    Lecture Notes in Computer Science, Vol. 1394, pp. 159-170, 1998.

  538. R. J. Hilderman and H. J. Hamilton
    Heuristic Measures of Interestingness
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 232-241, Springer, September 15-18 1999.

  539. R. J. Hilderman and H. J. Hamilton
    Heuristics for Ranking the Interestingness of Discovered Knowledge
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 204-209, Springer, April 26-28 1999.

  540. R. J. Hilderman and H. J. Hamilton
    Heuristics for Ranking the Interestingness of Discovered Knowledge
    Lecture Notes in Computer Science, Vol. 1574, pp. 204-209, 1999.

  541. R. Jiang and D. Li and H. Chen
    Time-Series Prediction with Cloud Models in DMKD
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, p. 525, Springer, April 26-28 1999.

  542. R. Jiang and D. Li and H. Chen
    Time-Series Prediction with Cloud Models in DMKD
    Lecture Notes in Computer Science, Vol. 1574, pp. 525-530, 1999.

  543. R. Kruse and C. Borgelt
    Data Mining with Graphical Models
    Lecture Notes in Computer Science, Vol. 1504, p. 3, 1998.

  544. R. M. Palenichka and M. A. Volgin
    Extraction of Local Structural Features in Images by Using a Multi-scale Relevance Function
    Proceedings of the 1st International Workshop on Machine Learning and Data Mining in Pattern Recognition (MLDM-99), LNAI, Vol. 1715, pp. 87-102, Springer, September 16-18 1999.

  545. R. Mac Kinney-Romero and C. Giraud-Carrier
    Learning from Highly Structured Data by Decomposition
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 436-441, Springer, September 15-18 1999.

  546. R. MacKinney-Romero and C. Giraud-Carrier
    Learning from Highly Structured Data by Decomposition
    Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery (PKDD99), pp. 436-441, Springer-Verlag, September 1999.

  547. R. Ng and J. Han
    Efficient and effective clustering method for spatial data mining
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  548. R. Nock and M. Sebban and P. Jappy
    Experiments on a Representation-Independent Top-Down and Prune Induction Scheme
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 223-231, Springer, September 15-18 1999.

  549. R. Páircéir and S. McClean and B. Scotney
    Automated Discovery of Rules and Exceptions from Distributed Databases Using Aggregates
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 156-164, Springer, September 15-18 1999.

  550. R. Rakotomalala and S. Lallich and S. Di Palma
    Studying the Behavior of Generalized Entropy in Induction Trees Using a M-of-N Concept
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 510-517, Springer, September 15-18 1999.

  551. R. Sunil Choenni and Arno P. J. M. Siebes
    A framework for query optimization to support data mining
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  552. R. Sunil Choenni and Arno P. J. M. Siebes
    A framework for query optimization to support data mining
    Technical Report, CWI - Centrum voor Wiskunde en Informatica, Number CS-R9637, October 31, 1996.

  553. R. T. Edwards and D. L. Dowe
    Single Factor Analysis in MML Mixture Modelling
    Lecture Notes in Computer Science, Vol. 1394, pp. 96-100, 1998.

  554. R. T. Ng and J. Han
    Efficient and Effective Clustering Methods for Spatial Data Mining
    20th International Conference on Very Large Data Bases, September 12--15, 1994, Santiago, Chile proceedings, pp. 144-155, Morgan Kaufmann Publishers, 1995.

  555. Rakesh Agrawal
    Data Mining
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  556. Rakesh Agrawal
    Data Mining: Crossing the Chasm
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 2-2, ACM Press, August 15-18 1999.

  557. Rakesh Agrawal
    Data Mining: The Quest Perspective
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  558. Rakesh Agrawal
    Tutorial: Data Mining
    PODS '94. Proceedings of the Thirteenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, May 24--26, 1994, Minneapolis, MN, Vol. 13, pp. 75-76, ACM Press, 1994.

  559. Rakesh Agrawal and Giuseppe Psaila
    Active Data Mining
    1st Int. Conf. Knowledge Discovery and Data Mining KDD,, pp. 3-8, AAAI Press, 20-21 August 1995.

  560. Rakesh Agrawal and Johannes E. Gehrke and Dimitrios Gunopulos and Prabhakar Raghavan
    Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications
    SIGMOD Record: Proc. ACM SIGMOD Int. Conf. Management of Data, 27(2), pp. 94-105, 2-4 June 1998.

  561. Rakesh Agrawal and Johannes Gehrke and Dimitrios Gunopulos and Prabhakar Raghavan
    Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications
    Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD-98), ACM SIGMOD Record, Vol. 27,2, pp. 94-105, ACM Press, June 1-4 1998.

  562. Rakesh Agrawal and Manish Mehta and John C. Shafer and Ramakrishnan Srikant and Andreas Arning and Toni Bollinger
    The Quest Data Mining System
    Proc. 2nd Int. Conf. Knowledge Discovery and Data Mining, KDD, pp. 244-249, AAAI Press, 2-4 August 1996.

  563. Ramakrishnan and Grama
    Data Mining: From Serendipity to Science
    COMPUTER: IEEE Computer, Vol. 32, 1999.

  564. Randall M. Rohrer and John L. Silbert and David S. Ebert
    A Shape-based Visual Interface for Text Retrieval
    IEEE Computer Graphics and Applications, 19(5), pp. 40-46, September 1999.

  565. Raymond T. Ng and Jiawei Han
    Efficient and Effective Clustering Methods for Spatial Data Mining
    Technical Report, Department of Computer Science, University of British Columbia, Number TR-94-13, May 1994.

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  566. Richard Hackathorn
    Farming the Web for Systematic Business Intelligence
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 3-3, ACM Press, August 15-18 1999.

  567. Robert Cooley and Bamshad Mobasher and Jaideep Srivastava
    Data Preparation for Mining World Wide Web Browsing Patterns
    Knowledge and Information Systems, 1(1), Springer-Verlag, February 1999.

  568. Robert E. Marmelstein
    GRaCCE: A Genetic Environment for Data Mining
    Late Breaking Papers at the Genetic Programming 1998 Conference, Stanford University Bookstore, 22-25 July 1998.

  569. Robert Evan Marmelstein
    Evolving Compact Decision Rule Sets
    PhD Thesis, Faculty of the Graduate School of Engineering of the Air Force Institute of Technology Air University, June 1999.

  570. Robert F. Cromp and William J. Campbell
    Data Mining of Multi-dimensional Remotely Sensed Images
    Proceedings of the 2nd International Conference on Information and Knowledge Management, pp. 471-480, ACM Press, November 1993.

  571. Robert L. Grossman and Stuart M. Bailey and Harinath Sivakumar and Andrei L. Turinsky
    Papyrus: A System for Data Mining over Local and Wide-area Clusters and Super-clusters
    SC'99: Oregon Convention Center 777 NE Martin Luther King Jr. Boulevard, Portland, Oregon, November 11--18, 1999, ACM Press and IEEE Computer Society Press, 1999.

  572. Roberto Bayardo and Rakesh Agrawal
    Mining the Most Interesting Rules
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 145-154, ACM Press, August 15-18 1999.

  573. Roddick (panel chair)
    Data Warehousing and Data Mining -- Are We Working on the Right Things?
    ER: Advances in Database Technologies: ER '98 Workshops on Data Warehousing and Data Mining, Mobile Data Access, and Collaborative Work Support and Spatio-Temporal Data Management, LNCS, 1998.

  574. Ron Kohavi and Sommerfield Dan
    Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology
    First International Conference on Knowledge Discovery and Data Mining (KDD-95), August 1995.

  575. Ronen Feldman
    Pratical Text Mining
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 478-478, Springer, September 23-26 1998.

  576. Rudolf Kruse and Christian Borgelt
    Data Mining with Graphical Models
    Proceedings of the 22nd Annual German Conference on Advances in Artificial Intelligence (KI-98), LNAI, Vol. 1504, pp. 3-16, Springer, September 15-17 1998.

  577. S. Augier and G. Venturini and Y. Kodratoff
    Learning first order logic rules with a genetic algorithm
    The First International Conference on Knowledge Discovery and Data Mining, pp. 21-26, AAAI Press, 20-21 August 1995.

  578. S. Ben Yahia and A. Jaoua
    BRRA: A Based Relevant Rectangle Algorithm for Mining Relationships in Databases
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 515-519, Springer, April 26-28 1999.

  579. S. Ben Yahia and A. Jaoua
    BRRA: A Based Relevant Rectangle Algorithm for Mining Relationships in Databases
    Lecture Notes in Computer Science, Vol. 1574, pp. 515-519, 1999.

  580. S. C. Yoon and I. Y. Song and E. K. Park
    Intensional Query Processing Using Data Mining Approaches
    Proceedings of the 6th International Conference on Information and Knowledge Management (CIKM-97), pp. 201-208, ACM Press, November 10-14 1997.

  581. S. Choenni
    On the Suitability of Genetic-Based Algorithms for Data Mining
    Lecture Notes in Computer Science, Vol. 1552, pp. 55-67, 1999.

  582. S. Dzeroski and P. Flach (eds.)
    Proceedings of the Ninth International Workshop on Inductive Logic Programming (ILP'99), Lecture Notes in Artificial Intelligence, Vol. 1634, Springer-Verlag, June 1999.

  583. S. Goil and A. Choudhary
    High Performance Data Mining using Data Cubes on Parallel Computers
    Proceedings of the 1st Merged International Parallel Processing Symposium and Symposium on Parallel and Distributed Processing (IPPS/SPDP-98), pp. 548-555, IEEE Computer Society, March 30- apr 3 1998.

  584. S. Guillaume and F. Guillet and J. Philippé
    Improving the Discovery of Association Rules with Intensity of Implication
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 318-327, Springer, September 23-26 1998.

  585. S. Köhler and M. Krieger
    The ESPRIT Project CreditMine and Its Relevance for the Internet Market
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 584-585, Springer, September 15-18 1999.

  586. S. Kramer and B. Pfahringer and C. Helma
    Mining for Causes of Cancer: Machine Learning Experiments at Various Levels of Detail
    Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), AAAI Press, 1997.

  587. S. Lallich
    ZigZag, a New Clustering Algorithm to Analyze Categorical Variable Cross-Classification Tables
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 398-405, Springer, September 15-18 1999.

  588. S. Lodi and L. Reami and C. Sartori
    Efficient Shared Near Neighbours Clustering of Large Metric Data Sets
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 424-429, Springer, September 15-18 1999.

  589. S. Lopes and J.-M. Petit and F. Toumani
    Discovery of Interesting Data Dependencies from a Workload of SQL Statements
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 430-435, Springer, September 15-18 1999.

  590. S. M. Monzurur Rahman and Xinghuo Yu and Geoff Martin
    Neural Network Approach for Data Mining
    Progress in Connectionsist-Based Information Systems. Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, Vol. 2, pp. 851-854, Springer, 1997.

  591. S. Massa and P. P. Puliafito
    An Application of Data Mining to the Problem of the University Students´ Dropout Using Markov Chains
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 51-60, Springer, September 15-18 1999.

  592. S. Muggleton
    Declarative knowledge discovery in industrial databases
    Proceedings of the First International Conference and Exhibition on The Practical Application of Knowledge Discovery and Data Mining (PADD-97), pp. 9-24, Practical Application Company Ltd., 1997.

  593. S. Nestorov and S. Tsur
    Integrating Data Mining with Relational DBMS: A Tightly-Coupled Approach
    Lecture Notes in Computer Science, Vol. 1649, p. 295, 1999.

  594. S. O. Kuznetsov
    Learning of Simple Conceptual Graphs from Positive and Negative Examples
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 384-391, Springer, September 15-18 1999.

  595. S. Reese Hedberg
    Parallelism speeds data mining
    IEEE parallel and distributed technology: systems and applications, 3(4), pp. 3-6, Winter 1995.

  596. S. S. Anand and D. A. Bell and J. G. Hughes and C. M. Shapcott
    A High-Performance Data Mining Server
    Lecture Notes in Computer Science, Vol. 1067, p. 907, 1996.

  597. S. S. Anand and D. Patterson and J. G. Hughes and Bell and D. A.
    Discovering Case Knowledge Using Data Mining
    Lecture Notes in Computer Science, Vol. 1394, pp. 25-35, 1998.

  598. S. S. Anand and J. G. Hughes
    Hybrid Data Mining Systems: The Next Generation
    Lecture Notes in Computer Science, Vol. 1394, pp. 13-24, 1998.

  599. S. Sugaya and E. Suzuki and S. Tsumoto
    Support Vector Machines for Knowledge Discovery
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 561-567, Springer, September 15-18 1999.

  600. S. Tsumoto
    Automated Discovery of Plausible Rules Based on Rough Sets and Rough Inclusion
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 210-219, Springer, April 26-28 1999.

  601. S. Tsumoto
    Automated Discovery of Plausible Rules Based on Rough Sets and Rough Inclusion
    Lecture Notes in Computer Science, Vol. 1574, pp. 210-219, 1999.

  602. S. Tsumoto
    Discovery of Approximate Medical Knowledge Based on Rough Set Model
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 468-476, Springer, September 23-26 1998.

  603. S. Tsumoto
    Knowledge Discovery in Medical Multi-databases: A Rough Set Approach
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 147-155, Springer, September 15-18 1999.

  604. S. Tsumoto
    Rule Discovery in Databases with Missing Values Based on Rough Set Model
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 274-278, Springer, April 26-28 1999.

  605. S. Tsumoto
    Rule Discovery in Databases with Missing Values Based on Rough Set Model
    Lecture Notes in Computer Science, Vol. 1574, pp. 274-278, 1999.

  606. S. Tsumoto
    Rule Discovery in Large Time-Series Medical Databases
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 23-31, Springer, September 15-18 1999.

  607. S. Tsumoto and W. Ziarko
    The application of rough sets-based data mining technique to differential diagnosis of meningoenchepahlitis
    Proceedings of the Ninth International Symposium on Foundations of Intelligent Systems, LNAI, Vol. 1079, pp. 438-447, Springer, June 9-13 1996.

  608. S. Tsumoto and W. Ziarko
    The application of rough sets-based data mining technique to differential diagnosis of meningoenchephalitis
    Lecture Notes in Computer Science, Vol. 1079, p. 438, 1996.

  609. Saharon Rosset and Uzi Murad and Einat Neumann and Yizhak Idan and Gadi Pinkas
    Discovery Of Fraud Rules for Telecommunications - Challenges and Solutions
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 409-413, ACM Press, August 15-18 1999.

  610. Salvatore Stolfo and David Fan and Andreas Prodromidis and Wenke Lee and Shelley Tselepsis and Philip Chan
    Agent-based Fraud and Intrusion Detection in Financial Information Systems
    , November 1997.

  611. Samuel Kaski
    Data Exploration using Self-Organizing Maps
    PhD Thesis, Helsinki University of Technology, March 1997.

  612. Sarabjot S. Anand and John G. Hughes
    Hybrid Data Mining Systems: The Next Generation
    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. 13-24, Springer, 15-17 April 1998.

  613. Scott Davies and Andrew Moore
    Bayesian Networks for Lossless Dataset Compression
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 387-391, ACM Press, August 15-18 1999.

  614. Scott Gaffney and Padhraic Smyth
    Trajectory Clustering with Mixtures of Regression Models
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 63-72, ACM Press, August 15-18 1999.

  615. Se June Hong and Sholom M. Weiss
    Advances in Predictive Data Mining Methods
    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.

  616. Sergey Brin
    Extracting Patterns and Relations from the World Wide Web
    WebDB Workshop at 6th International Conference on Extending Database Technology, EDBT'98, 1998.

  617. Sergey Brin and Lawrence Page
    Dynamic Data Mining: A New Architecture for Data with High Dimensionality
    Technical Report, Stanford University, 1998.

  618. Sergey Brin and Rajeev Rastogi and Kyuseok Shim
    Mining Optimized Gain Rules for Numeric Attributes
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 135-144, ACM Press, August 15-18 1999.

  619. Seth Rogers and Pat Langley and Christopher Wilson
    Mining GPS Data to Augment Road Models
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 104-113, ACM Press, August 15-18 1999.

  620. Shaun Saxon and Alwyn Barry
    XCS and the Monk's problem
    Proceedings of the 1999 Genetic and Evolutionary Computation Conference Workshop Program, pp. 272-281, 1999.

  621. Shin-Chung Shao
    Multivariate and Multidimensional OLAP
    Proc. 6th Int. Conf. Extending Database Technology EDBT,, Lecture Notes in Computer Science, LNCS, Vol. 1377, Springer-Verlag, 23-27 March 1998.

  622. Sigal Sahar
    Interestingness Via What Is Not Interesting
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 332-336, ACM Press, August 15-18 1999.

  623. Simon Thompson
    Genetic algorithms as postprocessors for data mining
    Data Mining with Evolutionary Algorithms: Research Directions, pp. 18-22, AAAI Press, 18 July 1999.

  624. Soumen Chakrabarti
    Hypertext Databases and Data Mining
    Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMod-99), SIGMOD Record, Vol. 28,2, pp. 508-508, ACM Press, June 1-3 1999.

  625. Srinivasan Parthasarathy and Mohammed Javeed Zaki and Wei Li
    Custom Memory Placement for Parallel Data Mining
    Technical Report, University of Rochester, Computer Science Department, Number TR653, November 1997.

  626. Stefan Escher
    Evaluation und Erweiterung eines Verfahrens zum Finden von Regelmässigkeiten in relationalen Datenbanken
    Diplomarbeit, Universität Stuttgart, Fakultät Informatik Germany,, Diplomarbeit 1444, p. 72, January 1997.

  627. Stefan Wrobel
    Data Mining und Wissensentdeckung in Datenbanken
    Künstliche Intelligenz, 12(1), pp. 6-10, 1998.

  628. Stefan Wrobel and Dietrich Wettschereck and A. Inkeri Verkamo and Arno Siebes and Heikki Mannila and Fred Kwakkel and Willi Klösgen
    User Interactivity in Very Large Scale Data Mining
    Proc. FGML-96 (Annual Meeting of the GI Special Interest Group Machine Learning), pp. 125-130, TU Chemnitz-Zwickau, August 1996.

  629. Stefan Wrobel and Dietrich Wettschereck and E. Sommer and Werner Emde
    Extensibility in Data Mining Systems
    Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining, p. 400, AAAI Press, 1997.

  630. Stefan Wrobel and Dietrich Wettschereck and Edgar Sommer and Werner Emde
    Extensibility in data mining systems
    Proc. 2nd International Conference On Knowledge Discovery and Data Mining, pp. 214-219, AAAI Press, August 1996.

  631. Stefan Wrobel and Saso Dzeroski
    The ILP description learning problem: Towards a general model-level definition of data mining in ILP
    Proc. Fachgruppentreffen Maschinelles Lernen (FGML-95), Univ. Dortmund, 1995.

  632. Stephen Bay and Michael Pazzani
    Detecting Change in Categorical Data: Mining Contrast Sets
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 302-306, ACM Press, August 15-18 1999.

  633. Stephen G. Eick and Brian S. Johnson
    Interactive Data Visualization at AT&T Bell Labs
    Proceedings of ACM CHI'95 Conference on Human Factors in Computing Systems, Demonstrations: Visualization, Vol. 2, pp. 17-18, 1995.

  634. Steven L. Salzberg
    On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach
    Data Mining and Knowledge Discovery, 1(3), 1997.

  635. Sunil Choenni
    Implementation and Evaluation of a Genetic-Based Data Mining Algorithm
    Technical Report, National Aerospace Laboratory, Number NLR-TR-99281, July 1999.

  636. Sunil Choenni
    On the Suitability of Genetic-Based Algorithms for Data Mining
    Advances in Database Technologies, LNCS, Vol. 1552, pp. 55-67, Springer, 19-20 November 1998.

  637. Sunil Choenni
    On the Suitability of Genetic-Based Algorithms for Data Mining
    Technical Report, National Aerospace Laboratory, Number NLR-TP-98484, November 1998.

  638. Sunil Choenni
    On the Suitability of Genetic-Based Algorithms for Data Mining
    Advances in Database Technologies, LNCS, Vol. 1552, pp. 55-67, Springer, 19-20 November 1998 1999.

  639. Surajit Chaudhuri and David Madigan (eds.)
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
    , ACM Press, August 15-18 1999.

  640. Sylvain Létourneau
    Data Mining for Maintenance of Complex Systems
    Proceedings of the 15th National Conference on Artificial Intelligence (AAAI-98) and of the 10th Conference on Innovative Applications of Artificial Intelligence (IAAI-98), pp. 1178-1178, AAAI Press, July 26-30 1998.

  641. T. Ågotnes and J. Komorowski and T. Løken
    Taming Large Rule Models in Rough Set Approaches
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 193-203, Springer, September 15-18 1999.

  642. T. B. Ho and N. B. Nguyen and T. Morita
    Study of a Mixed Similarity Measure for Classification and Clustering
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 375-379, Springer, April 26-28 1999.

  643. T. B. Ho and N. B. Nguyen and T. Morita
    Study of a Mixed Similarity Measure for Classification and Clustering
    Lecture Notes in Computer Science, Vol. 1574, pp. 375-379, 1999.

  644. T. B. Ho and T. D. Nguyen
    Interactive Visualization for Predictive Modelling with Decision Tree Induction
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 158-166, Springer, September 23-26 1998.

  645. T. Beran and T. Macek
    Recognition of Printed Music Score
    Proceedings of the 1st International Workshop on Machine Learning and Data Mining in Pattern Recognition (MLDM-99), LNAI, Vol. 1715, pp. 174-179, Springer, September 16-18 1999.

  646. T. Brijs and K. Vanhoof
    Cost Sensitive Discretization of Numeric Attributes
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 102-110, Springer, September 23-26 1998.

  647. T. C. Lin and M. Pourahmadi
    Nonparametric and non-linear models and data mining in time series: A case-study on the Canadian lynx data
    Applied Statistics, 47(2), p. 187, 1998.

  648. T. Edgoose and L. Allison
    Unsupervised Markov classification of sequence data using MML.
    Proc. 21st Australian Comp. Sci. Conf., pp. 81-94, Springer Verlag, February 1998.

  649. T. Elomaa and J. Rousu
    Postponing the Evaluation of Attributes with a High Number of Boundary Points
    Proceedings of the 2nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD-98), LNAI, Vol. 1510, pp. 221-229, Springer, September 23-26 1998.

  650. T. Elomaa and J. Rousu
    Speeding Up the Search for Optimal Partitions
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 89-97, Springer, September 15-18 1999.

  651. T. Fukuda and Y. Morimoto and S. Morishita and T. Tokuyama
    Interval Finding and Its Application to Data Mining
    Lecture Notes in Computer Science, Vol. 1178, p. 55, 1996.

  652. T. Imielinski and A. Virmani
    Association Rules... and What's Next? --- Towards Second Generation Data Mining Systems
    Lecture Notes in Computer Science, Vol. 1475, p. 6, 1998.

  653. T. Koshizen and H. Ogawa and J. Fulcher
    Empirical Results on Data Dimensionality Reduction Using the Divided Self-Organizing Map
    Lecture Notes in Computer Science, Vol. 1394, pp. 390-391, 1998.

  654. T. M. Vijayaraman and A. Buchmann and C. Mohan and N. L. Sarda (eds.)
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  655. T. Miyahara and T. Uchida and T. Kuboyama and T. Yamamoto
    KD-FGS: A Knowledge Discovery System from Graph Data Using Formal Graph System
    Lecture Notes in Computer Science, Vol. 1574, pp. 438-442, 1999.

  656. T. Miyahara and T. Uchida and T. Kuboyama and T. Yamamoto and K. Takahashi and H. Ueda
    KD-FGS: A Knowledge Discovery System from Graph Data Using Formal Graph System
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 438-442, Springer, April 26-28 1999.

  657. T. Mollestad and A. Skowron
    A rough set framework for data mining of propositional default rules
    Proceedings of the Ninth International Symposium on Foundations of Intelligent Systems, LNAI, Vol. 1079, pp. 448-457, Springer, June 9-13 1996.

  658. T. Mollestad and A. Skowron
    A rough set framework for data mining of propositional default rules
    Lecture Notes in Computer Science, Vol. 1079, p. 448, 1996.

  659. T. Okada
    Rule Induction in Cascade Model Based on Sum of Squares Decomposition
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 468-475, Springer, September 15-18 1999.

  660. T. Poddig and C. Huber
    Data Mining for the Detection of Turning Points in Financial Time Series
    Lecture Notes in Computer Science, Vol. 1642, p. 427, 1999.

  661. T. Poddig and K. Huber
    A Comparison of Model Selection Procedures for Predicting Turning Points in Financial Time Series
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 492-497, Springer, September 15-18 1999.

  662. T. Reinartz
    Similarity-Driven Sampling for Data Mining
    Lecture Notes in Computer Science, Vol. 1510, p. 423, 1998.

  663. T. Reinartz
    Similarity-Driven Sampling for Data Mining
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  664. T. Sawaragi
    Reproductive Process-Oriented Data Mining From Interactions between Human and Complex Artifact System
    Proceedings of the 1st International Workshop on Machine Learning and Data Mining in Pattern Recognition (MLDM-99), LNAI, Vol. 1715, pp. 180-194, Springer, September 16-18 1999.

  665. T. Shintani and M. Kitsuregawa
    Mining Algorithms for Sequential Patterns in Parallel: Hash Based Approach
    Lecture Notes in Computer Science, Vol. 1394, pp. 283-294, 1998.

  666. T. Wada and T. Horiuchi and H. Motoda and T. Washio
    Characterization of Default Knowledge in Ripple Down Rules Method
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 284-295, Springer, April 26-28 1999.

  667. T. Wada and T. Horiuchi and H. Motoda and T. Washio
    Characterization of Default Knowledge in Ripple Down Rules Method
    Lecture Notes in Computer Science, Vol. 1574, pp. 284-295, 1999.

  668. T. Washio and H. Matsuura and H. Motoda
    Mining Association Rules for Estimation and Prediction
    Lecture Notes in Computer Science, Vol. 1394, pp. 417-419, 1998.

  669. T. Wittmann and J. Ruhland and M. Eichholz
    Enhancing Rule Interestingness for Neuro-fuzzy Systems
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 242-250, Springer, September 15-18 1999.

  670. T. Y. Lin
    Data Mining: Granular Computing Approach
    Lecture Notes in Computer Science, Vol. 1574, pp. 24-33, 1999.

  671. T. Y. Lin
    Data Mining: Granular Computing Approach
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 24-33, Springer, April 26-28 1999.

  672. T. Yoshida and T. Kondo and S. Nishida
    Discovering Conceptual Differences among Different People via Diverse Structures
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 494-498, Springer, April 26-28 1999.

  673. T. Yoshida and T. Kondo and S. Nishida
    Discovering Conceptual Differences among Different People via Diverse Structures
    Lecture Notes in Computer Science, Vol. 1574, pp. 494-498, 1999.

  674. Takeshi Fukuda and Yasuhiko Morimoto and Shinichi Morishita and Takeshi Toluyama
    Data mining using two-dimensional optimized association rules: scheme, algorithms, and visualization
    SIGMOD Record (ACM Special Interest Group on Management of Data), 25(2), p. 13, 1996.

  675. Thomas Hofmann and Jan Puzicha
    Statistical Models for Co-occurrence Data
    Technical Report, Massachusetts Institute of Technology, Number AIM-1625, p. 21, December 1998.

  676. Tian Zhang and Raghu Ramakrishnan and Miron Livny
    BIRCH: A New Data Clustering Algorithm and its Applications
    Data Mining and Knowledge Discovery, 1(2), 1997.

  677. Tian Zhang and Raghu Ramakrishnan and Miron Livny
    Fast Density Estimation Using CF-Kernel for Very Large Databases
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 312-316, ACM Press, August 15-18 1999.

  678. Tilman Patrick Walker
    Einsatzmoeglichkeiten Evolutionaerer Algorithmen im Data Mining
    Diplomarbeit, Universität Stuttgart, Fakultät Informatik Germany,, Diplomarbeit 1500, p. 166, August 1997.

  679. Tim Oates
    Identifying Distinctive Subsequences in Multivariate Time Series by Clustering
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 322-326, ACM Press, August 15-18 1999.

  680. Tom Brijs and Gilbert Swinnen and Koen Vanhoof and Geert Wets
    Using Association Rules for Product Assortment Decisions: A Case Study
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 254-260, ACM Press, August 15-18 1999.

  681. Tom Fawcett and Foster Provost
    Activity Monitoring: Noticing Interesting Changes In Behavior
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 53-62, ACM Press, August 15-18 1999.

  682. Tom M. Mitchell
    Machine learning and data mining
    Communications of the ACM, 42(11), pp. 30-36, November 1999.

  683. Tremaine A. O. Cornish and Anthony D. Elliman
    What has Mill to Say About Data Mining ?
    Proceedings of the Eleventh Conference on Artificial Intelligence for Applications, pp. 347-353, IEEE Computer Society Press, February 20-22 1995.

  684. U. Murad and G. Pinkas
    Unsupervised Profiling for Identifying Superimposed Fraud
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 251-261, Springer, September 15-18 1999.

  685. Udo Grimmer
    Clementine: Data Mining Software
    Classification and Multivariate Graphics: Models Software and Applications,, Weierstrass-Institut für Angewandte Analysis und Stochastik, Number 10, pp. 25-31, 1996.

  686. Usama M. Fayyad & O. L. mangasarian, P. S. Bradley
    Data Mining: Overview and Optimization Opportunities
    Technical Report, University of Wisconsin, Madison, Number MP-TR-1998-01, January 1998.

  687. Usama M. Fayyad and Gregory Piatetsky-Shapiro and Padhr Smyth and Ramasamy Uthurusamy (eds.)
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  688. V. Cho and B. Wuethrich
    Combining Forecasts from Multiple Textual Data Sources
    Lecture Notes in Computer Science, Vol. 1574, pp. 174-178, 1999.

  689. V. Cho and B. Wuethrich
    Towards Real Time Discovery from Distributed Information Sources
    Lecture Notes in Computer Science, Vol. 1394, pp. 376-377, 1998.

  690. V. Cho and B. Wüthrich
    Combining Forecasts from Multiple Textual Data Sources
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 174-178, Springer, April 26-28 1999.

  691. V. Estivill-Castro and A. Murray
    Spatial Clustering for Data Mining with Genetic Algorithms
    Technical Report, Queensland University of Technology. Faculty of Information Technology, Number FIT-TR-97-10, September 1, 1997.

  692. V. Estivill-Castro and A. Murray
    Spatial Clustering for Data Mining with Genetic Algorithms
    Technical Report, Faculty of Information Technology, Queensland University of Technology, Number FIT-TR-97-10, September 01 1997.

  693. V. Estivill-Castro and A. T. Murray
    Discovering Associations in Spatial Data --- An Efficient Medoid Based Approach
    Lecture Notes in Computer Science, Vol. 1394, pp. 110-121, 1998.

  694. V. Estivill-Castro and M. E. Houle
    Robust Clustering of Large Geo-referenced Data Sets
    Proceedings of the 3rd Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining (PAKDD-99), LNAI, Vol. 1574, pp. 327-337, Springer, April 26-28 1999.

  695. V. Estivill-Castro and M. E. Houle
    Robust Clustering of Large Geo-referenced Data Sets
    Lecture Notes in Computer Science, Vol. 1574, pp. 327-337, 1999.

  696. V. Novacek
    Data Mining Extension for Object-Oriented Query Language
    Lecture Notes in Computer Science, Vol. 1521, p. 399, 1998.

  697. V. Novacek
    Data Mining Query Language for Object-Oriented Database
    Lecture Notes in Computer Science, Vol. 1475, p. 278, 1998.

  698. Valerie Issarny and Michel Banatre and Boris Charpiot and Jean-Marc Menaud
    Quality of Service and Electronic Newspaper: The Etel Solution
    Technical-Report, Inria, Institut National de Recherche en Informatique et en Automatique, p. 34 p..

  699. Valery Guralnik and Jaideep Srivastava
    Event Detection From Time Series Data
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 33-42, ACM Press, August 15-18 1999.

  700. Vasileios Megalooikonomou and Christos Davatzikos and Edward Herskovits
    Mining Lesion-Deficit Associations in a Brain Image Database
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 347-351, ACM Press, August 15-18 1999.

  701. Venkatesh Ganti and Johannes Gehrke and Raghu Ramakrishnan
    CACTUS: Clustering Categorical Data Using Summaries
    Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 73-83, ACM Press, August 15-18 1999.

  702. Vladimir A. Kulyukin and Kristian A. Hammond and Robin D. Burke
    Automated Processing of Structured Online Documents
    Technical Report, Department of Computer Science, University of Chicago, Number TR-98-02, February 27 1998.

  703. Vladimir Estivill-Castro and Alan T. Murray
    Discovering Associations in Spatial Data --- An Efficient Medoid Based Approach
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  704. W. B. Langdon
    Genetic Programming Approach to Benelearn 99: I
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  705. W. Ertel and M. Schramm
    Combining Data and Knowledge by MaxEnt-optimization of Probability Distributions
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 323-328, Springer, September 15-18 1999.

  706. W. H. Inmon
    The Data Warehouse and Data Mining
    Communications of the ACM, 39(11), pp. 49-50, November 1996.

  707. W. Kim
    KDD as an Enterprise IT Tool: Reality and Agenda
    Lecture Notes in Computer Science, Vol. 1574, p. 1, 1999.

  708. W. Kim
    KDD as an Enterprise IT Tool: Reality and Agenda
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  709. W. Kloesgen
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  710. W. Klösgen
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  711. W. Kowalczyk and Z. Piasta
    Rough Set-Inspired Approach to Knowledge Discovery in Business Databases
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  712. W. Kwedlo and M. Kr&ecedil;towski
    An Evolutionary Algorithm Using Multivariate Discretization for Decision Rule Induction
    Proceedings of the 3rd European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-99), LNAI, Vol. 1704, pp. 392-397, Springer, September 15-18 1999.

  713. W. Kwedlo and M. Kr&ecedil;towski
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  714. W. Traczyk
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  715. W. Traczyk
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  716. Wang Wei and Yang Jiong and Muntz Richard
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  717. Wei Fan and Salvatore J. Stolfo and Junxin Zhang
    The Application of Ada Boost for Distributed, Scalable and On-line Learning
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  718. Wei Wang and Jiong Yang and Richard Muntz
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  719. Wei Wang and Jiong Yang and Richard R. Muntz
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  720. Wei Wang Jiong Yang Richard Muntz
    PK-TREE: A DYNAMIC SPATIAL INDEXING STRUCTURE FOR LARGE DATA SETS
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  721. Wenke Lee and Salvatore J. Stolfo and Kui W. Mok
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  722. Wenke Lee and Salvatore Stolfo
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  723. Wenke Lee and Salvatore Stolfo and Kui Mok
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  725. William DuMouchel and Chris Volinsky and Theodore Johnson and Corinna Cortes and Daryl Pregibon
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  726. William F. Punch and Douglas Zongker and Erik D. Goodman
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  727. William H. Hsu and William M. Pottenger and Michael Weige and Jie. Wu and Ting-Hao Yang
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  728. William H. Hsu and William M. Pottenger and Michael Welge and Jie Wu and Ting-Hao Yang
    Genetic Algorithms for Attribute Synthesis in Large-Scale Data Mining
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  729. William Potts
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  730. William Ribarsky and Jochen Katz and Frank Jiang and Aubrey Holland
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  731. William W. Cohen and Haym Hirsh
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  732. Wolfgang Martin (ed.)
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  733. Wray Buntine and Bernd Fischer and Thomas Pressburger
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  734. X. Chen and I. Petrounias
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  735. X. Chen and I. Petrounias
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  737. X. Chen and I. Petrounias
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  738. X. Du and Z. Liu and N. Ishii
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  739. X. Du and Z. Liu and N. Ishii
    Mining Association Rules on Related Numeric Attributes
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  740. X. Meng and Y. Zhou and S. Wang
    Domain Knowledge Extracting in a Chinese Natural Language Interface to Databases: NChiql
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  741. X. Meng and Y. Zhou and S. Wang
    Domain Knowledge Extracting in a Chinese Natural Language Interface to Databases: NChiql
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  742. X. Polanco and C. François and M. A. Ould Louly
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  743. X. Shi and M.-C. Chan and D. Li
    Preserve Discovered Linguistic Patterns Valid in Volatility Data Environment
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  744. X. Shi and M.-C. Chan and D. Li
    Preserve Discovered Linguistic Patterns Valid in Volatility Data Environment
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  745. X. Tao and N. Wang and S. Zhou and A. Zhou
    Mining Functional Dependency Rule of Relational Database
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  747. X. Wang and R. Wang and J. Wang
    Sustainability Knowledge Mining from Human Development Database
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  748. X. Wang and R. Wang and J. Wang
    Sustainability Knowledge Mining from Human Development Database
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  751. X. Zhou and D. Truffet and J. Han
    Efficient Polygon Amalgamation Methods for Spatial OLAP and Spatial Data Mining
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  752. Xiaohua Hu and Nick Cercone
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  757. Y. Frayman and L. Wang
    Data Mining Using Dynamically Constructed Recurrent Fuzzy Neural Networks
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  759. Y. Guo and J. Sutiwaraphun
    Probing Knowledge in Distributed Data Mining
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  760. Y. Iizuka and H. Shiohara and T. Iizuka and S. Isobe
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  761. Y. Kakemoto and S. Nakasuka
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    A Situated Information Articulation Neural Network: VSF Network
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  765. Y. Lu and H. Liu and C. L. Tan
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  784. Z. R. Struzik and A. Siebes
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    Discovery of Equations and the Shared Operational Semantics in Distributed Autonomous Databases
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    Scaling Up the Rule Generation of C4.5
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  790. Z. Zheng and B. T. Low
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  792. Z. Zheng and C. I. Webb
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