Frequent Pattern Mining

This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference. An Introduction to Frequent Pattern Mining -- Frequent Pattern Mining Algorithms: A Survey -- Pattern-growth Methods -- Mining Long Patterns -- Interesting Patterns -- Negative Association Rules -- Constraint-based Pattern Mining -- Mining and Using Sets of Patterns through Compression -- Frequent Pattern Mining in Data Streams -- Big Data Frequent Pattern Mining -- Sequential Pattern Mining -- Spatiotemporal Pattern Mining: Algorithms and Applications -- Mining Graph Patterns -- Uncertain Frequent Pattern Mining -- Privacy in Association Rule Mining -- Frequent Pattern Mining Algorithms for Data Clustering -- Supervised Pattern Mining and Applications to Classification -- Applications of Frequent Pattern Mining. edited by Charu C. Aggarwal, Jiawei Han. Front Matter....Pages i-xix An Introduction to Frequent Pattern Mining....Pages 1-17 Frequent Pattern Mining Algorithms: A Survey....Pages 19-64 Pattern-Growth Methods....Pages 65-81 Mining Long Patterns....Pages 83-104 Interesting Patterns....Pages 105-134 Negative Association Rules....Pages 135-145 Constraint-Based Pattern Mining....Pages 147-163 Mining and Using Sets of Patterns through Compression....Pages 165-198 Frequent Pattern Mining in Data Streams....Pages 199-224 Big Data Frequent Pattern Mining....Pages 225-259 Sequential Pattern Mining....Pages 261-282 Spatiotemporal Pattern Mining: Algorithms and Applications....Pages 283-306 Mining Graph Patterns....Pages 307-338 Uncertain Frequent Pattern Mining....Pages 339-367 Privacy Issues in Association Rule Mining....Pages 369-401 Frequent Pattern Mining Algorithms for Data Clustering....Pages 403-423 Supervised Pattern Mining and Applications to Classification....Pages 425-442 Applications of Frequent Pattern Mining....Pages 443-467 Back Matter....Pages 469-471 Proposes numerous methods to solve some of the most fundamental problems in data mining and machine learning Presents various simplified perspectives, providing a range of information to benefit both students and practitioners Includes surveys on key research content, case studies and future research directions This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more