COBRA: Closed sequential pattern mining using Bi-phase reduction approach

Kuo Yu Huang, Chia Hui Chang, Jiun Hung Tung, Cheng Tao Ho

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations

Abstract

In this work, we study the problem of closed sequential pattern mining. We propose a novel approach which extends a frequent sequence with closed itemsets instead of single items. The motivation is that closed sequential patterns are composed of only closed itemsets. Hence, unnecessary item extensions which generates non-closed sequential patterns can be avoided. Experimental evaluation shows that the proposed approach is two orders of magnitude faster than previous works with a modest memory cost.

Original languageEnglish
Title of host publicationData Warehousing and Knowledge Discovery - 8th International Conference, DaWaK 2006, Proceedings
PublisherSpringer Verlag
Pages280-291
Number of pages12
ISBN (Print)3540377360, 9783540377368
DOIs
StatePublished - 2006
Event8th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2006 - Krakow, Poland
Duration: 4 Sep 20068 Sep 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4081 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2006
Country/TerritoryPoland
CityKrakow
Period4/09/068/09/06

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