Efficient mining of correlated sequential patterns based on null hypothesis

Cindy Xide Lin, Ming Ji, Marina Danilevsky, Jiawei Han

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Frequent pattern mining has been a widely studied topic in the research area of data mining for more than a decade. However, pattern mining with real data sets is complicated - a huge number of co-occurrence patterns are usually generated, a majority of which are either redundant or uninformative. The true correlation relationships among data objects are buried deep among a large pile of useless information. To overcome this difficulty, mining correlations has been recognized as an important data mining task for its many advantages over mining frequent patterns. In this paper, we formally propose and define the task of mining frequent correlated sequential patterns from a sequential database. With this aim in mind, we re-examine various interestingness measures to select the appropriate one(s), which can disclose succinct relationships of sequential patterns. We then propose PSBSpan, an efficient mining algorithm based on the framework of the pattern-growth methodology which mines frequent correlated sequential patterns. Our experimental study on real datasets shows that our algorithm has outstanding performance in terms of both efficiency and effectiveness.

Original languageEnglish (US)
Title of host publicationWeb-KR'12 - Proceedings of the 2012 ACM International Workshop on Web-Scale Knowledge Representation, Retrieval and Reasoning, Co-located with CIKM 2012
Pages17-24
Number of pages8
DOIs
StatePublished - Dec 7 2012
Event2012 3rd ACM International Workshop on Web-Scale Knowledge Representation, Retrieval, and Reasoning, Web-KR 2012, Co-located with the 21st ACM International Conference on Information and Knowledge Management, CIKM 2012 - Maui, HI, United States
Duration: Oct 29 2012Oct 29 2012

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other2012 3rd ACM International Workshop on Web-Scale Knowledge Representation, Retrieval, and Reasoning, Web-KR 2012, Co-located with the 21st ACM International Conference on Information and Knowledge Management, CIKM 2012
CountryUnited States
CityMaui, HI
Period10/29/1210/29/12

Keywords

  • Correlated pattern mining
  • Frequent pattern mining

ASJC Scopus subject areas

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

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