Sequential pattern mining -- approaches and algorithms

  • Authors:
  • Carl H. Mooney;John F. Roddick

  • Affiliations:
  • Flinders University, South Australia;Flinders University, South Australia

  • Venue:
  • ACM Computing Surveys (CSUR)
  • Year:
  • 2013

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Abstract

Sequences of events, items, or tokens occurring in an ordered metric space appear often in data and the requirement to detect and analyze frequent subsequences is a common problem. Sequential Pattern Mining arose as a subfield of data mining to focus on this field. This article surveys the approaches and algorithms proposed to date.