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Indexed by:期刊论文

Date of Publication:2012-02-01

Journal:Journal of Convergence Information Technology

Included Journals:EI、Scopus

Volume:7

Issue:3

Page Number:77-83

ISSN No.:19759320

Abstract:Nowadays, for subsequence retrieval, the time series are mostly divided by windows and indexed, respectively, according to the window size. As an example of human motion sequences, this article introduces Limited-SLCSS retrieval on time series based on the associated multi-indexes model. First, the symbolic human motion sequences are divided into disjoint windows according to the window size, and then they are stored into the associated multi-indexes. Then, the relevant windows of the query motion sequence are searched in the corresponding relevant inverted indexes with the dynamic programming algorithm, and the intersection operation is made in the resultant human motion sequences. Finally, the experiments prove that this method saves more space than the existing multi-indexes method, and this study improves the retrieval efficiency in comparison with the retrieval method on irrelevant multi-indexes.