Improvements of IncSpan: Incremental mining of sequential patterns in large database

Nguyen, Son N., Sun, Xingzhi and Orlowska, Maria E. (2005). Improvements of IncSpan: Incremental mining of sequential patterns in large database. In: Tu Bao Ho, David Cheung and Huan Liu, Proceedings of the 9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2005). 9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2005), Hanoi, Vietnam, (442-451). 18-20 May 2005. doi:10.1007/11430919_52

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Author Nguyen, Son N.
Sun, Xingzhi
Orlowska, Maria E.
Title of paper Improvements of IncSpan: Incremental mining of sequential patterns in large database
Conference name 9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2005)
Conference location Hanoi, Vietnam
Conference dates 18-20 May 2005
Proceedings title Proceedings of the 9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2005)   Check publisher's open access policy
Journal name Advances in Knowledge Discovery and Data Mining   Check publisher's open access policy
Place of Publication Heidelberg, Germany
Publisher Springer
Publication Year 2005
Sub-type Fully published paper
DOI 10.1007/11430919_52
Open Access Status DOI
ISBN 9783540260769
3540260765
ISSN 0302-9743
Editor Tu Bao Ho
David Cheung
Huan Liu
Volume 3518
Start page 442
End page 451
Total pages 10
Language eng
Formatted Abstract/Summary
In reality, sequence databases are updated incrementally. The changes on the database may invalidate some existing sequential patterns and introduce new ones. Instead of recomputing the database each time, the incremental mining algorithms target efficiently maintaining the sequential patterns in the dynamically changing database.
Recently, a new incremental mining algorithm, called IncSpan was proposed at the International Conference on Knowledge Discovery and Data Mining (KDD’04). However, we find that in general, IncSpan fails to mine the complete set of sequential patterns from an updated database. In this paper, we clarify this weakness by proving the incorrectness of the basic properties in the IncSpan algorithm. Also, we rectify the observed shortcomings by giving our solution.
Keyword Sequential patterns
Incremental mining
Algorithm
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Conference Paper
Sub-type: Fully published paper
Collections: School of Information Technology and Electrical Engineering Publications
2006 Higher Education Research Data Collection
 
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Citation counts: TR Web of Science Citation Count  Cited 11 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 18 times in Scopus Article | Citations
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Created: Fri, 24 Aug 2007, 07:01:02 EST