The conference program consists of 2 tutorials, 3 invited talks, 1 panel discussion, 1 pre-conference workshop, and a number of technical sessions for refereed paper presentations. The topic of the panel discussion is `To What Extent Can Data Mining Be Proceduralised?', and the theme of the workshop is `Parallel and Distributed Data Mining'. The 2 tutorials are `Data Mining: An Overview from Database Perspective' and `Applications of Minimum Message Length in Data Analysis'.
Of the 110 submissions, PAKDD-98 accepted 31 regular papers; an acceptance rate of 28%. In addition, over 20 papers were accepted as posters for short presentations. The technical sessions include: Data Mining in Temporal and Spatial Data; Rough Sets, Fuzzy Logic and Neural Networks; Induction of Rules and Decision Trees; Agent and Internet Based Mining; New Tools and Algorithms for Data Mining; Advanced Topics in Data Mining; Commercial Applications of Data Mining; and Minimum Message Length Inference (MML). The conference proceedings is published by Springer-Verlag as a book, titled `Research and Development in Knowledge Discovery and Data Mining' (Lecture Notes in Artificial Intelligence 1394).
April 15, Wednesday: -------------------- Tutorials (Room 1): Morning (9.00am - 12.00 noon): Chris Wallace (Monash University, Australia), Applications of Minimum Message Length in Data Analysis Afternoon (2.00pm - 5.00pm): Jiawei Han (Simon Fraser University, Canada), Data Mining: An Overview from Database Perspective Pre-Conference Workshop on Parallel and Distributed Data Mining (Room 2) 8.45am - 5:45pm: http://ruby.doc.ic.ac.uk/workshop/programme.html PAKDD Steering Committee Meeting: 6.00pm April 16, Thursday: ------------------- 8:30am - 8:45am (Room 1) Introduction: Ross Quinlan and Bala Srinivasan, Conference Chairs 8:45 - 9:45 am (Room 1) ACSys Keynote Talk: Jiawei Han OLAP Mining: An Integration of Data Mining and Data Warehousing Technologies 9:45am - 10:00am Break 10.00am - 12.00 noon Parallel Session 1 (Room 1): S4A: Data Mining in Temporal and Spatial Data Session Chair: David Cheung, Hong Kong University - Selective Materialization: An Efficient Method for Spatial Data Cube Construction by J. Han, N. Stefanovic and K. Koperski - Discovery of Association Rules over Ordinal Data: A New and Faster Algorithm and its Application to Basket Analysis by O. Buchter and R. Wirth - Discovering Associations in Spatial Data -- An Efficient Medoid Based Approach by V. Estivill-Castro and A. T. Murray - Mining Algorithms for Sequential Patterns in Parallel: Hash Based Approach by T. Shintani and M. Kitsuregawa - Data-Mining Massive Time Series Astronomical Data Sets -- a Case Study (Short Paper) by M.K. Ng, Z. Huang, and M. Hegland Parallel Session 2 (Room 2): S4B: Rough Sets, Fuzzy Logic and Neural Networks Session Chair: Ning Zhong, Yamaguchi University - Data Mining Using Dynamically Constructed Recurrent Fuzzy Neural Networks by Y. Frayman and L. Wang - Rough Set-Inspired Approach to Knowledge Discovery in Business Databases by W. Kowalczyk and Z. Piasta - Data Mining Based on the Generalization Distribution Table and Rough Sets by N. Zhong, J. Dong and S. Ohsuga 12.00 - 1.30pm: Lunch (Business Meeting at 1.00pm - 1.30pm, Room 1) 1.30pm - 3.00pm Parallel Session 1 (Room 1): S3A: Advanced Topics in Data Mining (1) Session Chair: Honghua Dai, The University of New England - Hybrid Data Mining Systems: The Next Generation by S. S. Anand and J. G. Hughes - Effect of Data Skewness in Parallel Mining of Association Rules by D. W. Cheung and Y. Xiao - Identifying Relevant Databases for Multidatabase Mining by H. Liu, H. Lu and J. Yao Parallel Session 2 (Room 2): S3B: Induction of Rules and Decision Trees (1) Session Chair: Zijian Zheng, Deakin University - Representative Association Rules by M. Kryszkiewicz - Bayesian Classification Trees with Overlapping Leaves Applied to Credit-Scoring by G. Paass and J. Kindermann - Treatment of missing values for association rules by A. Ragel and B. Cremilleux 3.00pm - 4.00pm Parallel Session 1 (Room 1): S2A: Agent and Internet Based Mining (Short Papers) Session Chair: Olivier de Vel, James Cook University - The Hunter and the Hunted -- Modelling the Relationship between Web Pages and Search Engines by D. L. Dowe, L. Allison and G. Pringle - Constructing Personalized Information Agents by C. H. Chang and C. C. Hsu Parallel Session 2 (Room 2): S2B: New Tools and Algorithms for Data Mining (1) Session Chair: John Zeleznikow, La Trobe University - CCAIIA: Clustering Categorical Attributes into Interesting Association Rules by B. Gray and M. E. Orlowska - Constructing Conceptual Scales in Formal Concept Analysis (Short Paper) by R. Cole, P. Eklund and D. Walker 4.00pm - 4.30pm: Break 4.30pm - 6.00pm Parallel Session 1 (Room 1): S3C: Minimum Message Length Inference (MML) Session Chair: Kevin Korb, Monash University - Point Estimation Using the Kullback-Leibler Loss Function and MML by D. L. Dowe, R. A. Baxter, J. J. Oliver and C. S. Wallace - Single Factor Analysis in MML Mixture Modelling by R. T. Edwards and D. L. Dowe - Minimum Message Length Segmentation by J. J. Oliver, R. A. Baxter and C.S. Wallace Parallel Session 2 (Room 2): S3D: Induction of Rules and Decision Trees (Short Papers) Session Chair: Huan Liu, National University of Singapore - An Efficient Global Discretization Method by K. M. Ho and P. D. Scott - CFMD: A Conflict-Free Multivariate Discretization Algorithm by Y. Lu, H. Liu and C. L. Tan - Characteristic Rule Induction Algorithm for Data Mining by A. Maeda, H. Maki and H. Akimori - Modelling Decision Tables from Data by J. Vanthienen and H. Timmermans - Mining Association Rules for Estimation and Prediction by T. Washio, H. Matsuura and H. Motoda 7.00pm: Conference Dinner April 17, Friday: ----------------- 8:30am - 8:45am (Room 1) Introduction: Xindong Wu and Kotagiri Ramamohanarao, Program Chairs 8:45 - 9:45 am (Room 1) Invited Talk: Chris Wallace Intrinsic Classification with Spatial Correlation 9:45am - 10:00am Break 10.00am - 12.00 noon Parallel Session 1 (Room 1): S4C: Commercial Applications of Data Mining Session Chair: Graham Williams, CSIRO - Mining Market Basket Data Using Share Measures and Characterized Itemsets by R. J. Hilderman, C. L. Carter, H. J. Hamilton and N. Cercone - Knowledge Acquisition for Goal Prediction in a Multi-User Adventure Game by D. W. Albrecht, A. E. Nicholson and I. Zukerman - Discovering Case Knowledge Using Data Mining by S. S. Anand, D. Patterson, J. G. Hughes and D.A. Bell - Knowledge Discovery in Discretionary Legal Domains by J. Zeleznikow and A. Stranieri - Design Recovery with Data Mining Techniques (Short Paper) by C. Montes de Oca and D. L. Carver Parallel Session 2 (Room 2): S4D: Induction of Rules and Decision Trees (2) Session Chair: Hiroshi Motoda, Osaka University - Mining Regression Rules and Regression Trees by B. Y. Sher, S. C. Shao and W. S. Hsieh - Improved Rule Discovery Performance on Uncertainty by M. R. Tolun, H. Sever and M. Uludag - Scaling Up the Rule Generation of C4.5 by Z. Zheng - Interestingness of Discovered Association Rules in Terms of Neighborhood-Based Unexpectedness by G. Dong and J. Li 12.00 - 1.15pm: Lunch 1.15pm - 2.15pm (Room 1) Invited Talk: Bhavani Thuraisingham Data Warehousing, Data Mining, and Security 2.15pm - 3:15pm Parallel Session 1 (Room 1): S2C: Advanced Topics in Data Mining (Short Papers) Session Chair: Yike Guo, Imperial College - Towards Real Time Discovery from Distributed Information Sources by V. Cho and B. Wuthrich - Multiple Databases, Partial Reasoning, and Knowledge Discovery by C. Nowak - A Data Mining Approach for Query Refinement by Y. Liu, H. Chen, J. X. Yu and N. Ohbo Parallel Session 2 (Room 2): S2D: New Tools and Algorithms for Data Mining (2) Session Chair: Hongjun Lu, National University of Singapore - Trend Directed Learning: A Case Study by H. Dai - Feature Mining and Mapping of Collinear Data by O. de Vel, D. Coomans and S. Patrick 3.15pm - 4.15pm Parallel Session 1 (Room 1): S2E: Advanced Topics in Data Mining (2) Session Chair: Ming Zhao, Telstra - Wavelet Transform in Similarity Paradigm by Z. R. Struzik and A. Siebes - Automatic Visualization Method for Visual Data Mining by Y. Iizuka, H. Shiohara, T. Iizuka and S. Isobe Parallel Session 2 (Room 2): S2F: New Tools and Algorithms for Data Mining (Short Papers) Session Chair: Beat Wuthrich, Hong Kong University of Science and Technology - Empirical Results on Data Dimensionality Reduction Using the Divided Self-Organizing Map by T. Koshizen, H. Ogawa and J. Fulcher - The CLARET algorithm by A. Pearce and T. Caelli - LR Tree: A Hybrid Technique for Classifying Myocardial Infarction Data Containing Unknown Attribute Values by C. L. Tsien, H. S. F. Fraser and I. S. Kohane 4.15pm - 4.30pm: Break 4.30pm - 5:30pm Panel Discussion (Room 1) To What Extent Can Data Mining Be Proceduralised? Panel Chair: Ross Quinlan, RuleQuest Research Pty Ltd and UNSW 7:00pm Program Committee Dinner