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• W132159265 abstract "Previous chapter Next chapter Full AccessProceedings Proceedings of the 2008 SIAM International Conference on Data Mining (SDM)Efficiently Mining Closed Subsequences with Gap ConstraintsChun Li and Jianyong WangChun Li and Jianyong Wangpp.313 - 322Chapter DOI:https://doi.org/10.1137/1.9781611972788.28PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstract Mining frequent subsequence patterns from sequence databases is a typical data mining problem and various efficient sequential pattern mining algorithms have been proposed. In many problem domains (e.g, biology), the frequent subsequences confined by the predefined gap requirements are more meaningful than the general sequential patterns. In this paper we re-examine the closed sequential pattern mining problem by introducing the gap constraints. The most challenging parts in this task include the constrained pattern closure checking and unpromising search space pruning. Inspired by some state-of-the-art closed or constrained sequential pattern mining algorithms, we propose an efficient approach to finding the complete set of closed sequential patterns with gap constraints. The approach combines the newly devised constrained pattern closure checking scheme and pruning techniques with the pattern growth based subsequence enumeration framework. Our extensive performance study shows that our approach is very efficient in mining frequent closed subsequences with gap constraints. Previous chapter Next chapter RelatedDetails Published:2008ISBN:978-0-89871-654-2eISBN:978-1-61197-278-8 https://doi.org/10.1137/1.9781611972788Book Series Name:ProceedingsBook Code:PR130Book Pages:1-869Key words:Constrained subsequence mining, frequent closed subsequence, gap-constraint" @default.
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• W132159265 title "Efficiently Mining Closed Subsequences with Gap Constraints" @default.
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