Constraint-based sequential pattern mining: The pattern-growth methods

Jian Pei, Jiawei Han, Wei Wang

Research output: Contribution to journalArticlepeer-review

Abstract

Constraints are essential for many sequential pattern mining applications. However, there is no systematic study on constraint-based sequential pattern mining. In this paper, we investigate this issue and point out that the framework developed for constrained frequent-pattern mining does not fit our mission well. An extended framework is developed based on a sequential pattern growth methodology. Our study shows that constraints can be effectively and efficiently pushed deep into the sequential pattern mining under this new framework. Moreover, this framework can be extended to constraint-based structured pattern mining as well.

Original languageEnglish (US)
Pages (from-to)133-160
Number of pages28
JournalJournal of Intelligent Information Systems
Volume28
Issue number2
DOIs
StatePublished - Apr 2007

Keywords

  • Frequent pattern mining
  • Mining with constraints
  • Pattern-growth methods
  • Sequential pattern mining

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

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