Post-mining of association rules techniques for effective knowledge extraction /

• Corporate Author: IGI Global.
• Other Authors: Zhao, Yanchang, 1977-, Zhang, Chengqi, 1957-, Cao, Longbing, 1969-
• Format: Electronic
• Language: English
• Published: Hershey, Pa. : IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA), c2009.
• Subjects: Paired-association learning.; Association of ideas.; Data mining.; Association rules; Background knowledge for association; Classification results analyses; Data stream management system; Maintenance of association rules; Meta-knowledge based approach; New forms of association rules; Post-mining of association rules; Semantics-based classification; Variations on associative classifiers
• Online Access: View fulltext via EzAccess

"This book provides a systematic collection on the post-mining, summarization and presentation of association rule, as well as new forms of association rules"--Provided by publisher.

Table of Contents:

• Section I. Introduction
• 1. Association Rules: An Overview
• Section II. Identifying Interesting Rules
• 2. From Change Mining to Relevance Feedback: A Unified View on Assessing Rule Interestingness
• 3. Combining Data-Driven and User-Driven Evaluation Measures to Identify Interesting Rules
• 4. Semantics-Based Classification of Rule Interestingness Measures
• Section III. Post-Analysis and Post-Mining of Association Rules
• 5. Post-Processing for Rule Reduction Using Closed Set
• 6. A Conformity Measure Using Background Knowledge for Association Rules: Application to Text Mining
• 7. Continuous Post-Mining of Association Rules in a Data Stream Management System
• 8. QROC: A Variation of ROC Space to Analyze Item Set Costs/Benefits in Association Rules
• Section IV. Rule Selection for Classification
• 9. Variations on Associative Classifiers and Classification Results Analyses
• 10. Selection of High Quality Rules in Associative Classification
• Section V. Visualization and Representation of Association Rules
• 11. Meta-Knowledge Based Approach for an Interactive Visualization of Large Amounts of Association Rules
• 12. Visualization to Assist the Generation and Exploration of Association Rules
• 13. Frequent Closed Itemsets Based Condensed Representations for Association Rules
• Section VI. Maintenance of Association Rules and New Forms of Association Rules
• 14. Maintenance of Frequent Patterns: A Survey
• 15. Mining Conditional Contrast Patterns
• 16. Multidimensional Model-Based Decision Rules Mining
• Compilation of References
• About the Contributors
• Index.