Knowledge Discovery and Data Mining. Current Issues and New Applications: Current Issues and New Applications: 4th Pacific-Asia Conference, PAKDD 2000 Kyoto, Japan, April 18-20, 2000 Proceedings

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Takao Terano, Huan Liu, Arbee L.P. Chen
Springer Science & Business Media, 2007 M07 13 - 462 pages
The Fourth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2000) was held at the Keihanna-Plaza, Kyoto, Japan, April 18 - 20, 2000. PAKDD 2000 provided an international forum for researchers and applica tion developers to share their original research results and practical development experiences. A wide range of current KDD topics were covered including ma chine learning, databases, statistics, knowledge acquisition, data visualization, knowledge-based systems, soft computing, and high performance computing. It followed the success of PAKDD 97 in Singapore, PAKDD 98 in Austraha, and PAKDD 99 in China by bringing together participants from universities, indus try, and government from all over the world to exchange problems and challenges and to disseminate the recently developed KDD techniques. This PAKDD 2000 proceedings volume addresses both current issues and novel approaches in regards to theory, methodology, and real world application. The technical sessions were organized according to subtopics such as Data Mining Theory, Feature Selection and Transformation, Clustering, Application of Data Mining, Association Rules, Induction, Text Mining, Web and Graph Mining. Of the 116 worldwide submissions, 33 regular papers and 16 short papers were accepted for presentation at the conference and included in this volume. Each submission was critically reviewed by two to four program committee members based on their relevance, originality, quality, and clarity.
 

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Contents

Keynote Speeches and Invited Talk
1
Fast Discovery of Interesting Rules
17
Minimum Message Length Criterion for SecondOrder Polynomial Model
40
Frequent Closures as a Concise Representation for Binary Data Mining
62
Exception Rule Mining with a Relative Interestingness Measure
86
Feature Selection for Clustering
110
Missing Value Estimation Based on Dynamic Attribute Selection
134
A Visual Method of Cluster Validation with Fastmap
153
DensityBased Mining of Quantitative Association Rules
257
Discovering Unordered and Ordered Phrase Association Patterns for Text
281
Using Random Walks for Mining Web Document Associations
294
Scaling Up a BoostingBased Learner via Adaptive Sampling
317
Robust Ensemble Learning for Data Mining
341
Making Knowledge Extraction and Reasoning Closer
360
Efficient and Comprehensible Local Regression
376
Mining Access Patterns Efficiently from Web Logs
396

Combining Sampling Technique with DBSCAN Algorithm for Clustering
169
Efficient Detection of Local Interactions in the Cascade Model
193
Evaluating HypothesisDriven ExceptionRule Discovery with Medical
208
Mining Structured Association Patterns from Databases
233
Extension of GraphBased Induction for General Graph Structured Data
420
Extraction of Fuzzy Clusters from Weighted Graphs
442
Author Index
459
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