Sequential patterns mining scaling with data stream based on LSP-tree

Authors:
Qinhua Huang;Weimin Ouyang
Affiliations:
Modern Education Technology Center, Shanghai University of Political Science and Law, Shanghai, China;Modern Education Technology Center, Shanghai University of Political Science and Law, Shanghai, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
Year:
2009

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Abstract

We present a new method of mining sequential patterns in data stream based on a fast bitmap method. In recent years data stream emerges as a new data type in many applications. When processing data stream, the memory is fixed, new stream elements flow continuously. The stream data can not be paused or completely stored. We developed a LSPtree data structure to store the discovered sequential patterns. To be suitable for the time-changing stream data, a time-tilted window is applied to scale with continuously increased LSP-tree. Experiments on a set of large data stream demonstrate the utility of this algorithm.