Mining sequential patterns with constraints in large databases

  • Authors:
  • Jian Pei;Jiawei Han;Wei Wang

  • Affiliations:
  • State University of New York at Buffalo;Univ. of Illinois at Urbana-Champaign;Fudan University

  • Venue:
  • Proceedings of the eleventh international conference on Information and knowledge management
  • Year:
  • 2002

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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 missions 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 sequential pattern mining under this new framework. Moreover, this framework can be extended to constraint-based structured pattern mining as well.