DocumentCode :
1732412
Title :
Mining Frequent Patterns with Gaps and One-Off Condition
Author :
Huang, Yongming ; Wu, Xindong ; Hu, Xuegang ; Xie, Fei ; Gao, Jun ; Wu, Gongqing
Author_Institution :
Sch. of Comput. Sci. & Inf. Eng., Hefei Univ. of Technol., Hefei, China
Volume :
1
fYear :
2009
Firstpage :
180
Lastpage :
186
Abstract :
Mining frequent patterns with a gap requirement from sequences is an important step in many domains, such as biological sciences. Given a character sequence S of length L, a certain threshold and a gap constraint, we aim to discover frequent patterns whose supports in S are no less than the given threshold value. A frequent pattern P can have wildcards, and the numbers of the wildcards between elements of P must fulfill user-specified gap constraints. Also, this mining process satisfies the one-off condition and an apriori-like property to be efficient. Experiments show that our method can mine as many frequent patterns with wildcards as the existing MPP algorithm, but has a much better performance in time.
Keywords :
DNA; biology computing; data mining; DNA sequence; apriori-like property; biological sciences; frequent pattern mining; one-off condition; AC generators; Biological system modeling; Biology; Computer science; DNA; Data analysis; Data mining; Indexing; Sequences; Transaction databases; data mining; frequent patterns; gaps; one-off condition; wildcards;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Science and Engineering, 2009. CSE '09. International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-5334-4
Electronic_ISBN :
978-0-7695-3823-5
Type :
conf
DOI :
10.1109/CSE.2009.160
Filename :
5282959
Link To Document :
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