Advances in Knowledge Discovery and Data Mining: 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001. Proceedings

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David Cheung, Graham J. Williams, Qing Li
Springer Science & Business Media, Apr 4, 2001 - Computers - 599 pages
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This book constitutes the refereed proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2001, held in Hong Kong, China in April 2001.
The 38 revised full papers and 22 short papers presented were carefully reviewed and selected from a total of 152 submissions. The book offers topical sections on Web mining, text mining, applications and tools, concept hierarchies, feature selection, interestingness, sequence mining, spatial and temporal mining, association mining, classification and rule induction, clustering, and advanced topics and new methods.
 

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Contents

Incompleteness in Data Mining
1
The Good the Bad and the Ugly
2
Seamless Integration of Data Mining with DBMS and Applications
3
Applying Pattern Mining to Web Information Extraction
4
Empirical Study of Recommender Systems Using Linear Classifiers
16
iJADE eMiner A WebBased Mining Agent Based on Intelligent Java Agent Development Environment iJADE on Internet Shopping
28
A Characterized Rating Recommend System
41
Discovery of Frequent Tree Structured Patterns in Semistructured Web Documents
47
An Index Structure for Subsequence Matching of Spatial Objects
312
Temporal Data Mining Using Hidden MarkovLocal Polynomial Models
324
Patterns Discovery Based on TimeSeries Decomposition
336
Criteria on Proximity Graphs for Boundary Extraction and Spatial Clustering
348
Micro Similarity Queries in Time Series Database
358
Mining Optimal Class Association Rule Set
364
Generating Frequent Patterns with the Frequent Pattern List
376
UserDefined Association Mining
387

Text Categorization Using Weight Adjusted kNearest Neighbor Classification
53
Predictive SelfOrganizing Networks for Text Categorization
66
Metalearning Models for Automatic Textual Document Categorization
78
Efficient Algorithms for Concept Space Construction
90
Topic Detection Tracking and Trend Analysis Using SelfOrganizing Neural Networks
102
Automatic Hypertext Construction through a Text Mining Approach by SelfOrganizing Maps
108
A Study on Hong Kong Stock Movement Analysis
114
A Toolbox Approach to Flexible and Efficient Data Mining
124
Determining Progression in Glaucoma Using Visual Fields
136
Seabreeze Prediction Using Bayesian Networks
148
Semisupervised Learning in Medical Image Database
154
On Application of Rough Data Mining Methods to Automatic Construction of Student Models
161
Concept Approximation in Concept Lattice
167
Mining Additional Semantics in Relational Data
174
Representing Large Concept Hierarchies Using Lattice Data Structure
186
Feature Selection for Temporal Health Records
198
Boosting the Performance of Nearest Neighbour Methods with Feature Selection
210
Feature Selection for Metalearning
222
Efficient Mining of Niches and Set Routines
234
Evaluation of Interestingness Measures for Ranking Discovered Knowledge
247
Peculiarity Oriented Mining and Its Application for Knowledge Discovery in AminoAcid Data
260
Mining Sequence Patterns from Wind Tunnel Experimental Data for Flight Control
270
Scalable Hierarchical Clustering Method for Sequences of Categorical Values
282
FFS An IOEfficient Algorithm for Mining Frequent Sequences
294
Sequential Index Structure for ContentBased Retrieval
306
Direct and Incremental Computing of Maximal Covering Rules
400
Towards Efficient Data Remining DRM
406
Data Allocation Algorithm for Parallel Association Rule Discovery
413
Direct Domain Knowledge Inclusion in the PA3 Rule Induction Algorithm
421
Hierarchical Classification of Documents with Error Control
433
An Efficient Data Compression Approach to the Classification Task
444
Combining the Strength of Pattern Frequency and Distance for Classification
455
A Scalable Algorithm for Rule Postpruning of Large Decision Trees
467
Optimizing the Induction of Alternating Decision Trees
477
Building Behaviour Knowledge Space to Make Classification Decision
488
Efficient Hierarchical Clustering Algorithms Using Partially Overlapping Partitions
495
A Rough SetBased Clustering Method with Modification of Equivalence Relations
507
Importance of Individual Variables in the kMeans Algorithm
513
A Hybrid Approach to Clustering in Very Large Databases
519
A Similarity Indexing Method for the Data Warehousing BitWise Indexing Method
525
Rule Reduction over Numerical Attributes in Decision Tree Using Multilayer Perceptron
538
Knowledge Acquisition from Both Human Expert and Data
550
Neighborhood Dependencies for Prediction
562
Learning Bayesian Networks with Hidden Variables Using the Combination of EM and Evolutionary Algorithms
568
Interactive Construction of Decision Trees
575
An Improved Learning Algorithm for Augmented Naive Bayes
581
Generalised RBF Networks Trained Using an IBL Algorithm for Mining Symbolic Data
587
Author Index
594
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About the author (2001)

Qing Li is a principal engineer for Wind River Systems, Inc. with extensive experience in designing and developing applications for embedded biometric devices, protocol stacks, and applications for telecommunications and networks.