Association Rule Mining: Models and Algorithms (Lecture Notes in Computer Science (2307))

Due To The Popularity Of Knowledge Discovery And Data Mining, In Practice As Well As Among Academic And Corporate R&d Professionals, Association Rule Mining Is Receiving Increasing Attention. The Authors Present The Recent Progress Achieved In Mining Quantitative Association Rules, Causal Rules, Exceptional Rules, Negative Association Rules, Association Rules In Multi-databases, And Association Rules In Small Databases. This Book Is Written For Researchers, Professionals, And Students Working In The Fields Of Data Mining, Data Analysis, Machine Learning, Knowledge Discovery In Databases, And Anyone Who Is Interested In Association Rule Mining. Association Rule -- Negative Association Rule -- Causality In Databases -- Causal Rule Analysis -- Association Rules In Very Large Databases -- Association Rules In Small Databases -- Conclusion And Future Work. Chengqi Zhang, Shichao Zhang. Includes Bibliographical References (p. [229]-236) And Index. Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R & D professionals, association rule mining is receiving increasing attention. The authors present the recent progress achieved in mining quantitative association rules, causal rules, exceptional rules, negative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining Introduction....Pages 1-23 Association Rule....Pages 25-46 Negative Association Rule....Pages 47-84 Causality in Databases....Pages 85-120 Causal Rule Analysis....Pages 121-159 Association Rules in Very Large Databases....Pages 161-198 Association Rules in Small Databases....Pages 199-224 Conclusion and Future Work....Pages 225-228