Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction, 1st Edition

  • Published By:
  • ISBN-10: 1605664057
  • ISBN-13: 9781605664057
  • Grade Level Range: College Freshman - College Senior
  • 372 Pages | eBook
  • Original Copyright 2009 | Published/Released August 2009
  • This publication's content originally published in print form: 2009

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Provides a systematic collection on post-mining, summarization and presentation of association rules, and new forms of association rules. Presents researchers, practitioners, and academicians with tools to extract useful and actionable knowledge after discovering a large number of association rules.

Table of Contents

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