Graph-based Modelling of Concurrent Sequential Patterns

Jing Lu, Weiru Chen, Malcolm Keech

Research output: Contribution to journalArticlepeer-review


Structural relation patterns have been introduced recently to extend the search for complex patterns often hidden behind large sequences of data. This has motivated a novel approach to sequential patterns post-processing and a corresponding data mining method was proposed for Concurrent Sequential Patterns (ConSP). This article refines the approach in the context of ConSP modelling, where a companion graph-based model is devised as an extension of previous work. Two new modelling methods are presented here together with a construction algorithm, to complete the transformation of concurrent sequential patterns to a ConSP-Graph representation. Customer orders data is used to demonstrate the effectiveness of ConSP mining while synthetic sample data highlights the strength of the modelling technique, illuminating the theories developed.
Original languageEnglish
Pages (from-to)41-58
Number of pages18
JournalInternational Journal of Data Warehousing and Mining
Issue number2
Publication statusPublished - 2010
Externally publishedYes


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