Frequent pattern mining

Bibliographic Information

Frequent pattern mining

Charu C. Aggarwal, Jiawei Han, editors

Springer, c2014

Available at  / 5 libraries

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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"

Details

  • NCID
    BB16782776
  • ISBN
    • 9783319078205
  • Country Code
    sz
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Cham
  • Pages/Volumes
    xix, 471 p.
  • Size
    25 cm
  • Classification
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