DocumentCode :
3267981
Title :
BIDE: efficient mining of frequent closed sequences
Author :
Wang, Jianyong ; Han, Jiawei
Author_Institution :
Illinois Univ., Urbana, IL, USA
fYear :
2004
fDate :
30 March-2 April 2004
Firstpage :
79
Lastpage :
90
Abstract :
Previous studies have presented convincing arguments that a frequent pattern mining algorithm should not mine all frequent patterns but only the closed ones because the latter leads to not only more compact yet complete result set but also better efficiency. However, most of the previously developed closed pattern mining algorithms work under the candidate maintenance-and-test paradigm which is inherently costly in both runtime and space usage when the support threshold is low or the patterns become long. We present, BIDE, an efficient algorithm for mining frequent closed sequences without candidate maintenance. We adopt a novel sequence closure checking scheme called bidirectional extension, and prunes the search space more deeply compared to the previous algorithms by using the BackScan pruning method and the Scan-Skip optimization technique. A thorough performance study with both sparse and dense real-life data sets has demonstrated that BIDE significantly outperforms the previous algorithms: it consumes order(s) of magnitude less memory and can be more than an order of magnitude faster. It is also linearly scalable in terms of database size.
Keywords :
data mining; optimisation; search problems; BIDE; BackScan pruning method; Scan-Skip optimization technique; bidirectional extension; frequent closed sequence; pattern mining algorithm; search space; sequence closure checking; Bidirectional control; Computer science; Data mining; Databases; Itemsets; Optimization methods; Pattern analysis; Proteins; Runtime; XML;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering, 2004. Proceedings. 20th International Conference on
ISSN :
1063-6382
Print_ISBN :
0-7695-2065-0
Type :
conf
DOI :
10.1109/ICDE.2004.1319986
Filename :
1319986
Link To Document :
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