Knowledge discovery and data mining have become areas of growing significance because of the recent increasing demand for KDD techniques, including those used in machine learning, databases, statistics, knowledge acquisition, data visualization, and high performance computing. In view of this, and following the success of the five previous PAKDD conferences, the sixth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2002) aimed to provide a forum for the sharing of original research results, innovative ideas, state-of-the-art developments, and implementation experiences in knowledge discovery and data mining among researchers in academic and industrial organizations. Much work went into preparing a program of high quality. We received 128 submissions. Every paper was reviewed by 3 program committee members, and 32 were selected as regular papers and 20 were selected as short papers, representing a 25% acceptance rate for regular papers. The PAKDD 2002 program was further enhanced by two keynote speeches, delivered by Vipin Kumar from the Univ. of Minnesota and Rajeev Rastogi from AT&T. In addition, PAKDD 2002 was complemented by three tutorials, XML and data mining (by Kyuseok Shim and Surajit Chadhuri), mining customer data across various customer touchpoints at- commerce sites (by Jaideep Srivastava), and data clustering analysis, from simple groupings to scalable clustering with constraints (by Osmar Zaiane and Andrew Foss).
Author(s): Minos Garofalakis, Rajeev Rastogi (auth.), Ming-Syan Chen, Philip S. Yu, Bing Liu (eds.)
Series: Lecture Notes in Computer Science 2336 : Lecture Notes in Artificial Intelligence
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2002
Language: English
Pages: 570
Tags: Artificial Intelligence (incl. Robotics); Database Management; Probability and Statistics in Computer Science; Statistics and Computing/Statistics Programs; Computers and Society
Privacy Preserving Data Mining: Challenges and Opportunities....Pages 1-12
A Case for Analytical Customer Relationship Management....Pages 13-13
On Data Clustering Analysis: Scalability, Constraints, and Validation....Pages 14-27
Discovering Numeric Association Rules via Evolutionary Algorithm....Pages 28-39
Efficient Rule Retrieval and Postponed Restrict Operations for Association Rule Mining....Pages 40-51
Association Rule Mining on Remotely Sensed Images Using P-trees....Pages 52-65
On the Efficiency of Association-Rule Mining Algorithms....Pages 66-79
A Function-Based Classifier Learning Scheme Using Genetic Programming....Pages 80-91
SNNB: A Selective Neighborhood Based Naïve Bayes for Lazy Learning....Pages 92-103
A Method to Boost Naïve Bayesian Classifiers....Pages 104-114
Toward Bayesian Classifiers with Accurate Probabilities....Pages 115-122
Pruning Redundant Association Rules Using Maximum Entropy Principle....Pages 123-134
A Confidence-Lift Support Specification for Interesting Associations Mining....Pages 135-147
Concise Representation of Frequent Patterns Based on Generalized Disjunction-Free Generators....Pages 148-158
Mining Interesting Association Rules: A Data Mining Language....Pages 159-171
The Lorenz Dominance Order as a Measure of Interestingness in KDD....Pages 172-176
Efficient Algorithms for Incremental Update of Frequent Sequences....Pages 177-185
DELISP: Efficient Discovery of Generalized Sequential Patterns by Delimited Pattern-Growth Technology....Pages 186-197
Self-Similarity for Data Mining and Predictive Modeling A Case Study for Network Data....Pages 198-209
A New Mechanism of Mining Network Behavior....Pages 210-217
M-FastMap: A Modified FastMap Algorithm for Visual Cluster Validation in Data Mining....Pages 218-223
An Incremental Hierarchical Data Clustering Algorithm Based on Gravity Theory....Pages 224-236
Adding Personality to Information Clustering....Pages 237-250
Clustering Large Categorical Data....Pages 251-256
WebFrame: In Pursuit of Computationally and Cognitively Efficient Web Mining....Pages 257-263
Naviz :Website Navigational Behavior Visualizer....Pages 264-275
Optimal Algorithms for Finding User Access Sessions from Very Large Web Logs....Pages 276-289
Automatic Information Extraction for Multiple Singular Web Pages....Pages 290-296
An Improved Approach for the Discovery of Causal Models via MML....Pages 297-303
SETM*-MaxK: An Efficient SET-Based Approach to Find the Largest Itemset....Pages 304-315
Discovery of Ordinal Association Rules....Pages 316-321
Value Added Association Rules....Pages 322-327
Top Down FP-Growth for Association Rule Mining....Pages 328-333
Discovery of Frequent Tag Tree Patterns in Semistructured Web Documents....Pages 334-340
Extracting Characteristic Structures among Words in Semistructured Documents....Pages 341-355
An Efficient Algorithm for Incremental Update of Concept Spaces....Pages 356-367
Efficient Constraint-Based Exploratory Mining on Large Data Cubes....Pages 368-380
Efficient Utilization of Materialized Views in a Data Warehouse....Pages 381-392
Mining Interesting Rules in Meningitis Data by Cooperatively Using GDT-RS and RSBR....Pages 393-404
Evaluation of Techniques for Classifying Biological Sequences....Pages 405-416
Efficiently Mining Gene Expression Data via Integrated Clustering and Validation Techniques....Pages 417-431
Adaptive Generalized Estimation Equation with Bayes Classifier for the Job Assignment Problem....Pages 432-437
GEC: An Evolutionary Approach for Evolving Classifiers....Pages 438-449
An Efficient Single-Scan Algorithm for Mining Essential Jumping Emerging Patterns for Classification....Pages 450-455
A Method to Boost Support Vector Machines....Pages 456-462
Distribution Discovery: Local Analysis of Temporal Rules....Pages 463-468
News Sensitive Stock Trend Prediction....Pages 469-480
User Profiling for Intrusion Detection Using Dynamic and Static Behavioral Models....Pages 481-493
Incremental Extraction of Keyterms for Classifying Multilingual Documents in the Web....Pages 494-505
k -nearest Neighbor Classification on Spatial Data Streams Using P-trees....Pages 506-516
Interactive Construction of Classification Rules....Pages 517-528
Enhancing Effectiveness of Outlier Detections for Low Density Patterns....Pages 529-534
Cluster-Based Algorithms for Dealing with Missing Values....Pages 535-548
Extracting Causation Knowledge from Natural Language Texts....Pages 549-554
Mining Relationship Graphs for Effective Business Objectives....Pages 555-560
....Pages 561-566
