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Methodologies for Knowledge Discovery and Data Mining : Third Pacific-Asia Conference, Pakdd'99, Beijing, China, April 26-28, 1999, Proceedings - Ning Zhong

Methodologies for Knowledge Discovery and Data Mining

Third Pacific-Asia Conference, Pakdd'99, Beijing, China, April 26-28, 1999, Proceedings

By: Ning Zhong (Editor), Lizhu Zhou (Editor)

Paperback Published: 14th April 1999
ISBN: 9783540658665
Number Of Pages: 540

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This volume contains the papers selected for presentation at the Third Paci?c- Asia Conference on Knowledge Discovery and Data Mining (PAKDD-99)held in the Xiangshan Hotel, Beijing, China, April 26-28, 1999. The conference was sp- sored by Tsinghua University, National Science Foundation of China, Chinese Computer Federation, Toshiba Corporation, and NEC Software Chugoku, Ltd. PAKDD-99 provided an international forum for the sharing of original research results and practical development experiences among researchers and application developers from di?erent KDD-related areas such as machine lea- ing, databases, statistics, knowledge acquisition, data visualization, knowled- based systems, soft computing, and high performance computing. It followed the success of PAKDD-97 held in Singapore in 1997 and PAKDD-98 held in A- tralia in 1998 by bringing together participants from universities, industry, and government. PAKDD-99 encouraged both new theory/methodologies and real world - plications, and covered broad and diverse topics in data mining and knowledge discovery. The technical sessions included: Association Rules Mining; Feature Selection and Generation; Mining in Semi, Un-structured Data; Interestingness, Surprisingness, and Exceptions; Rough Sets, Fuzzy Logic, and Neural Networks; Induction, Classi?cation, and Clustering; Causal Model and Graph-Based Me- ods; Visualization; Agent-Based, and Distributed Data Mining; Advanced Topics and New Methodologies. Of the 158 submissions, we accepted 29 regular papers and 37 short papers for presentation at the conference and for publication in this volume. In addition, over 20 papers were accepted for poster presentation.

Invited Talks
KDD as an Enterprise IT Tool: Reality and Agendap. 1
Computer Assisted Discovery of First Principle Equations from Numeric Datap. 2
Emerging KDD Technology
Data Mining: A Rough Set Perspectivep. 3
Data Mining Techniques for Associations, Clustering and Classificationp. 13
Data Mining: Granular Computing Approachp. 24
Rule Extraction from Prediction Modelsp. 34
Association Rules
Mining Association Rules on Related Numeric Attributesp. 44
LGen - A Lattice-Based Candidate Set Generation Algorithm for I/O Efficient Association Rule Miningp. 54
Extending the Applicability of Association Rulesp. 64
An Efficient Approach for Incremental Association Rule Miningp. 74
Association Rules in Incomplete Databasesp. 84
Parallel SQL Based Association Rule Mining on Large Scale PC Cluster: Performance Comparison with Directly Coded C Implementationp. 94
H-Rule Mining in Heterogeneous Databasesp. 99
An Improved Definition of Multidimensional, Inter-transaction Association Rulep. 104
Incremental Discovering Association Rules: A Concept Lattice Approachp. 109
Feature Selection and Generation
Induction as Pre-processingp. 114
Stochastic Attribute Selection Committees with Multiple Boosting: Learning More Accurate and More Stable Classifier Committeesp. 123
On Information-Theoretic Measures of Attribute Importancep. 133
A Technique of Dynamic Feature Selection Using the Feature Group Mutual Informationp. 138
A Data Pre-processing Method Using Association Rules of Attributes for Improving Decision Treep. 143
Mining in Semi, Un-structured Data
An Algorithm for Constrained Association Rule Mining in Semi-structured Datap. 148
Incremental Mining of Schema for Semi-structured Datap. 159
Discovering Structure from Document Databasesp. 169
Combining Forecasts from Multiple Textual Data Sourcesp. 174
Domain Knowledge Extracting in a Chinese Natural Language Interface to Databases: NChiqlp. 179
Interestingness, Surprisingness, and Exceptions
Evolutionary Hot Spots Data Mining: An Architecture for Exploring for Interesting Discoveriesp. 184
Efficient Search of Reliable Exceptionsp. 194
Heuristics for Ranking the Interestingness of Discovered Knowledgep. 204
Rough Sets, Fuzzy Logic, and Neural Networks
Automated Discovery of Plausible Rules Based on Rough Sets and Rough Inclusionp. 210
Discernibility System in Rough Setsp. 220
Automatic Labeling of Self-Organizing Maps: Making a Treasure-Map Reveal Its Secretsp. 228
Neural Network Based Classifiers for a Vast Amount of Datap. 238
Accuracy Tuning on Combinatorial Neural Modelp. 247
A Situated Information Articulation Neural Network: VSF Networkp. 252
Neural Method for Detection of Complex Patterns in Databasesp. 258
Preserve Discovered Linguistic Patterns Valid in Volatility Data Environmentp. 263
An Induction Algorithm Based on Fuzzy Logic Programmingp. 268
Rule Discovery in Databases with Missing Values Based on Rough Set Modelp. 274
Sustainability Knowledge Mining from Human Development Databasep. 279
Induction, Classification, and Clustering
Characterization of Default Knowledge in Ripple Down Rules Methodp. 284
Improving the Performance of Boosting for Naive Bayesian Classificationp. 296
Convex Hulls in Concept Inductionp. 306
Mining Classification Knowledge Based on Cloud Modelsp. 317
Robust Clustering of Large Geo-referenced Data Setsp. 327
A Fast Algorithm for Density-Based Clustering in Large Databasep. 338
A Lazy Model-Based Algorithm for On-Line Classificationp. 350
An Efficient Space-Partitioning Based Algorithm for the K-Means Clusteringp. 355
A Fast Clustering Process for Outliers and Remainder Clustersp. 360
Optimising the Distance Metric in the Nearest Neighbour Algorithm on a Real-World Patient Classification Problemp. 365
Classifying Unseen Cases with Many Missing Valuesp. 370
Study of a Mixed Similarity Measure for Classification and Clusteringp. 375
Visually Aided Exploration of Interesting Association Rulesp. 380
DVIZ: A System for Visualizing Data Miningp. 390
Causal Model and Graph-Based Methods
A Minimal Causal Model Learnerp. 400
Efficient Graph-Based Algorithm for Discovering and Maintaining Knowledge in Large Databasesp. 409
Basket Analysis for Graph Structured Datap. 420
The Evolution of Causal Models: A Comparison of Bayesian Metrics and Structure Priorsp. 432
KD-FGS: A Knowledge Discovery System from Graph Data Using Formal Graph Systemp. 438
Agent-Based, and Distributed Data Mining
Probing Knowledge in Distributed Data Miningp. 443
Discovery of Equations and the Shared Operational Semantics in Distributed Autonomous Databasesp. 453
The Data-Mining and the Technology of Agents to Fight the Illicit Electronic Messagesp. 464
Knowledge Discovery in SportsFinder: An Agent to Extract Sports Results from the Webp. 469
Event Mining with Event Processing Networksp. 474
Advanced Topics and New Methodologies
An Analysis of Quantitative Measures Associated with Rulesp. 479
A Strong Relevant Logic Model of Epistemic Processes in Scientific Discoveryp. 489
Discovering Conceptual Differences among Different People via Diverse Structuresp. 494
Ordered Estimation of Missing Valuesp. 499
Prediction Rule Discovery Based on Dynamic Bias Selectionp. 504
Discretization of Continuous Attributes for Learning Classification Rulesp. 509
BRRA: A Based Relevant Rectangle Algorithm for Mining Relationships in Databasesp. 515
Mining Functional Dependency Rule of Relational Databasep. 520
Time-Series Prediction with Cloud Models in DMKDp. 525
Author Indexp. 531
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9783540658665
ISBN-10: 3540658661
Series: Lecture Notes in Artificial Intelligence
Audience: General
Format: Paperback
Language: English
Number Of Pages: 540
Published: 14th April 1999
Publisher: Springer-Verlag Berlin and Heidelberg Gmbh & Co. Kg
Country of Publication: DE
Dimensions (cm): 23.39 x 15.6  x 2.87
Weight (kg): 0.77