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

Fingerprint

telecommunication
event
education

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

Applications of pattern discovery using sequential data mining. / Gupta, Manish; Han, Jiawei.

Pattern Discovery Using Sequence Data Mining: Applications and Studies. IGI Global, 2011. p. 1-23.

Research output: Chapter in Book/Report/Conference proceedingChapter

Gupta, M & Han, J 2011, Applications of pattern discovery using sequential data mining. in Pattern Discovery Using Sequence Data Mining: Applications and Studies. IGI Global, pp. 1-23. https://doi.org/10.4018/978-1-61350-056-9.ch001
Gupta M, Han J. Applications of pattern discovery using sequential data mining. In Pattern Discovery Using Sequence Data Mining: Applications and Studies. IGI Global. 2011. p. 1-23 https://doi.org/10.4018/978-1-61350-056-9.ch001
Gupta, Manish ; Han, Jiawei. / Applications of pattern discovery using sequential data mining. Pattern Discovery Using Sequence Data Mining: Applications and Studies. IGI Global, 2011. pp. 1-23
@inbook{6b79cb529d7a45c0929a04a3ca787522,
title = "Applications of pattern discovery using sequential data mining",
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.",
author = "Manish Gupta and Jiawei Han",
year = "2011",
month = "12",
day = "1",
doi = "10.4018/978-1-61350-056-9.ch001",
language = "English (US)",
isbn = "9781613500569",
pages = "1--23",
booktitle = "Pattern Discovery Using Sequence Data Mining",
publisher = "IGI Global",

}

TY - CHAP

T1 - Applications of pattern discovery using sequential data mining

AU - Gupta, Manish

AU - Han, Jiawei

PY - 2011/12/1

Y1 - 2011/12/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84897873944&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84897873944&partnerID=8YFLogxK

U2 - 10.4018/978-1-61350-056-9.ch001

DO - 10.4018/978-1-61350-056-9.ch001

M3 - Chapter

AN - SCOPUS:84897873944

SN - 9781613500569

SP - 1

EP - 23

BT - Pattern Discovery Using Sequence Data Mining

PB - IGI Global

ER -