DocumentCode
3228454
Title
Fast and efficient mining for frequent patterns on biological sequence
Author
Wei, Liu ; Ling, Chen
Author_Institution
Sch. of Inf. Technol., Nanjing Xiaozhuang Univ., Nanjing, China
fYear
2010
fDate
23-26 Sept. 2010
Firstpage
971
Lastpage
975
Abstract
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.
Keywords
bioinformatics; data mining; biological sequence; biological sequential data mining; pattern mining; prefix tree; Algorithm design and analysis; Computers; Proteins; biological sequence; frequent pattern mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location
Changsha
Print_ISBN
978-1-4244-6437-1
Type
conf
DOI
10.1109/BICTA.2010.5645133
Filename
5645133
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