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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 ch...

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Korporativní autor: SpringerLink (Online service)
Další autoři: Aggarwal, Charu C. (Editor, http://id.loc.gov/vocabulary/relators/edt), Han, Jiawei. (Editor, http://id.loc.gov/vocabulary/relators/edt)
Médium: Elektronický zdroj E-kniha
Jazyk:English
Vydáno: Cham : Springer International Publishing : Imprint: Springer, 2014.
Vydání:1st ed. 2014.
Témata:
Data mining.
Database management.
Artificial intelligence.
Pattern recognition.
Biometrics (Biology).
Data Mining and Knowledge Discovery.
Database Management.
Artificial Intelligence.
Pattern Recognition.
Biometrics.
On-line přístup:https://doi.org/10.1007/978-3-319-07821-2
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Obsah:
  • 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.

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