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:
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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:
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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:
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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
