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Quick-motif: An efficient and scalable framework for exact motif discovery
Li Y.1; Leong Hou U.1; Yiu M.L.2; Gong Z.1
2015
Conference Namethe ICDE 2015
Source PublicationProceedings - International Conference on Data Engineering
Volume2015-May
Pages579-590
Conference DateApril 13-16, 2015
Conference PlaceSeoul, Korea
Abstract

Discovering motifs in sequence databases has been receiving abundant attentions from both database and data mining communities, where the motif is the most correlated pair of subsequences in a sequence object. Motif discovery is expensive for emerging applications which may have very long sequences (e.g., million observations per sequence) or the queries arrive rapidly (e.g., per 10 seconds). Prior works cannot offer fast correlation computations and prune subsequence pairs at the same time, as these two techniques require different orderings on examining subsequence pairs. In this work, we propose a novel framework named Quick-Motif which adopts a two-level approach to enable batch pruning at the outer level and enable fast correlation calculation at the inner level. We further propose two optimization techniques for the outer and the inner level. In our experimental study, our method is up to 3 orders of magnitude faster than the state-of-the-art methods.

DOI10.1109/ICDE.2015.7113316
URLView the original
Language英语
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Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Universidade de Macau
2.Hong Kong Polytechnic University
Recommended Citation
GB/T 7714
Li Y.,Leong Hou U.,Yiu M.L.,et al. Quick-motif: An efficient and scalable framework for exact motif discovery[C],2015:579-590.
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