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Frequent Pattern Mining pp 19–64Cite as

Frequent Pattern Mining Algorithms: A Survey

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Abstract

This chapter will provide a detailed survey of frequent pattern mining algorithms. A wide variety of algorithms will be covered starting from Apriori. Many algorithms such as Eclat, TreeProjection, and FP-growth will be discussed. In addition a discussion of several maximal and closed frequent pattern mining algorithms will be provided. Thus, this chapter will provide one of most detailed surveys of frequent pattern mining algorithms available in the literature.

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Notes

  1. 1.

    The resulting FP-Tree will be a suffix-based trie.

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Authors and Affiliations

  1. IBM T. J.Watson Research Center, Yorktown Heights, NY, 10598, USA

    Charu C. Aggarwal

  2. Indiana University–Purdue University, Indianapolis, IN, USA

    Mansurul A. Bhuiyan & Mohammad Al Hasan

Authors
  1. Charu C. Aggarwal
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  2. Mansurul A. Bhuiyan
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  3. Mohammad Al Hasan
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Correspondence to Charu C. Aggarwal .

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Editors and Affiliations

  1. IBM, Yorktown Heights, New York, USA

    Charu C. Aggarwal

  2. University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

    Jiawei Han

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Aggarwal, C., Bhuiyan, M., Hasan, M. (2014). Frequent Pattern Mining Algorithms: A Survey. In: Aggarwal, C., Han, J. (eds) Frequent Pattern Mining. Springer, Cham. https://doi.org/10.1007/978-3-319-07821-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-07821-2_2

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