Mining sequential patterns with constraints in large databases

Jian Pei, Jiawei Han, Wei Wang

Research output: Contribution to conferencePaper

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.

Original languageEnglish (US)
Pages18-25
Number of pages8
StatePublished - Dec 1 2002
EventProceedings of the Eleventh International Conference on Information and Knowledge Management (CIKM 2002) - McLean, VA, United States
Duration: Nov 4 2002Nov 9 2002

Other

OtherProceedings of the Eleventh International Conference on Information and Knowledge Management (CIKM 2002)
CountryUnited States
CityMcLean, VA
Period11/4/0211/9/02

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ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

Cite this

Pei, J., Han, J., & Wang, W. (2002). Mining sequential patterns with constraints in large databases. 18-25. Paper presented at Proceedings of the Eleventh International Conference on Information and Knowledge Management (CIKM 2002), McLean, VA, United States.