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Fast and efficient mining for frequent patterns on biological sequence

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2 Author(s)
Liu Wei ; Sch. of Inf. Technol., Nanjing Xiaozhuang Univ., Nanjing, China ; Chen Ling

Biological sequential frequent pattern mining is one of the important research fields in biological sequential data mining. In order to overcome the shortcomings of traditional algorithms, we proposed a fast algorithm SSPM here. We used longer patterns and prefix tree of primary frequent patterns for mining which avoided plenty of irrelevant patterns. The experimental results show that our algorithm could not only improve the performance but also achieve effective mining results.

Published in:

Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on

Date of Conference:

23-26 Sept. 2010

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