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Parallel mining of closed sequential patterns
2005
Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining - KDD '05
Discovery of sequential patterns is an essential data mining task with broad applications. Among several variations of sequential patterns, closed sequential pattern is the most useful one since it retains all the information of the complete pattern set but is often much more compact than it. Unfortunately, there is no parallel closed sequential pattern mining method proposed yet. In this paper we develop an algorithm, called Par-CSP (Parallel Closed Sequential Pattern mining), to conduct
doi:10.1145/1081870.1081937
dblp:conf/kdd/CongHP05
fatcat:h5mdgsox2ndrxmts7ggmsfxn7i