Frequent pattern mining
Author(s)
Bibliographic Information
Frequent pattern mining
Springer, c2014
Available at / 5 libraries
-
No Libraries matched.
- Remove all filters.
Note
Including bibliographical references (p. 461-467) and index
Description and Table of Contents
Description
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.
Table of Contents
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.
by "Nielsen BookData"
