Frequent Pattern Mining [electronic resource] /
edited by Charu C. Aggarwal, Jiawei Han.
- XIX, 471 p. 83 illus., 19 illus. in color. online resource.
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.
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.
9783319078212
10.1007/978-3-319-07821-2 doi
Computer science. Database management. Data mining. Artificial intelligence. Pattern recognition. Biometrics (Biology). Computer Science. Data Mining and Knowledge Discovery. Database Management. Artificial Intelligence (incl. Robotics). Pattern Recognition. Biometrics.