Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction

There is often a large number of association rules discovered in data mining practice, making it difficult for users to identify those that are of particular interest to them. Therefore, it is important to remove insignificant rules and prune redundancy as well as summarize, visualize, and post-mine the discovered rules.

Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction provides a systematic collection on post-mining, summarization and presentation of association rules, and new forms of association rules. This book presents researchers, practitioners, and academicians with tools to extract useful and actionable knowledge after discovering a large number of association rules.

The many academic areas covered in this publication include, but are not limited to:

• 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