Abstract

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.

Original languageEnglish (US)
PublisherSpringer International Publishing
Number of pages471
Volume9783319078212
ISBN (Electronic)9783319078212
ISBN (Print)3319078208, 9783319078205
DOIs
StatePublished - Jul 1 2014

ASJC Scopus subject areas

  • Computer Science(all)

Fingerprint Dive into the research topics of 'Frequent pattern mining'. Together they form a unique fingerprint.

  • Cite this

    Aggarwal, C. C., & Han, J. (2014). Frequent pattern mining. Springer International Publishing. https://doi.org/10.1007/978-3-319-07821-2