Applications of pattern discovery using sequential data mining

Manish Gupta, Jiawei Han

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Sequential pattern mining methods have been found to be applicable in a large number of domains. Sequential data is omnipresent. Sequential pattern mining methods have been used to analyze this data and identify patterns. Such patterns have been used to implement efficient systems that can recommend based on previously observed patterns, help in making predictions, improve usability of systems, detect events, and in general help in making strategic product decisions. In this chapter, we discuss the applications of sequential data mining in a variety of domains like healthcare, education, Web usage mining, text mining, bioinformatics, telecommunications, intrusion detection, et cetera. We conclude with a summary of the work.

Original languageEnglish (US)
Title of host publicationPattern Discovery Using Sequence Data Mining
Subtitle of host publicationApplications and Studies
PublisherIGI Global
Pages1-23
Number of pages23
ISBN (Print)9781613500569
DOIs
StatePublished - Dec 1 2011

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ASJC Scopus subject areas

  • Social Sciences(all)

Cite this

Gupta, M., & Han, J. (2011). Applications of pattern discovery using sequential data mining. In Pattern Discovery Using Sequence Data Mining: Applications and Studies (pp. 1-23). IGI Global. https://doi.org/10.4018/978-1-61350-056-9.ch001