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http://dx.doi.org/10.3745/KIPSTD.2005.12D.6.807

Mining Frequent Closed Sequences using a Bitmap Representation  

Kim Hyung-Geun (강원대학교대학원 컴퓨터정보통신공학과)
Whang Whan-Kyu (강원대학교전지전자정보통신공학부)
Publication Information
The KIPS Transactions:PartD / v.12D, no.6, 2005 , pp. 807-816 More about this Journal
Abstract
Sequential pattern mining finds all of the frequent sequences satisfying a minimum support threshold in a large database. However, when mining long frequent sequences, or when using very low support thresholds, the performance of currently reported algorithms often degrades dramatically. In this paper, we propose a novel sequential pattern algorithm using only closed frequent sequences which are small subset of very large frequent sequences. Our algorithm generates the candidate sequences by depth-first search strategy in order to effectively prune. using bitmap representation of underlying databases, we can effectively calculate supports in terms of bit operations and prune sequences in much less time. Performance study shows that our algorithm outperforms the previous algorithms.
Keywords
Sequential Pattern Mining; Closed Sequential Pattern;
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