PAKDD-98 Advance Program

PAKDD-98 Advance Program


The Second Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-98) provides an international forum for the sharing of original research results and practical development experiences among researchers and application developers from different KDD related areas such as machine learning, databases, statistics, knowledge acquisition, data visualization, software re-engineering, and knowledge-based systems. It follows the success of PAKDD-97 held in Singapore in 1997 by bringing together participants from universities, industry and government.

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).

Advance Program

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:

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

9:45am - 10:00am

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
   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
   by Y. Frayman and L. Wang
 - Rough Set-Inspired Approach to Knowledge Discovery in Business
   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
   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
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
   by R. J. Hilderman, C. L. Carter, H. J. Hamilton and N. Cercone
 - Knowledge Acquisition for Goal Prediction in a Multi-User Adventure
   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

Program Committee Dinner