NDLI: Fuzzy sequential pattern mining with sliding window constraint

Content Provider	IEEE Xplore Digital Library
Author	Zabihi, F. Pedram, M.M. Ramezan, M. Memariani, A.
Copyright Year	2010
Description	Author affiliation: Industrial Engineering Department, Tarbiat Moallem University, Karaj/Tehran, Iran (Zabihi, F.) \|\| Computer Engineering Department, Tarbiat Moallem University, Karaj/Tehran, Iran (Pedram, M.M.; Ramezan, M.) \|\| Institute for Research and Planning in Higher Education, Tehran, Iran (Memariani, A.)
Abstract	Sequential pattern mining is to discover all subsequences that are frequent. The classical sequential pattern mining algorithms do not allow processing of numerical data and require preprocessing of these data into a binary representation, which necessarily leads to a loss of information. Fuzzy sets are used to overcome this problem. In present fuzzy sequential pattern mining algorithms, there isn't any matter of itemset time and sequences are only found based on sequence of happening. In this paper, a novel fuzzy sequential pattern algorithm is proposed with sliding window constraint which permits elements of a pattern to span a set of transactions within a user-specified window. Therefore, loss of useful sequences is prevented in the search process. The proposed algorithm searches for a goal sequence within the defined fuzzy sliding window and the membership degree of sliding window is returned if the goal sequence is found.
File Size	1465949
File Format	PDF
ISBN	9781424463671
e-ISBN	9781424463701
DOI	10.1109/ICETC.2010.5530044
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	fuzzy sequential pattern mining Lattices Educational technology Industrial engineering Transaction databases Data mining Technology planning sliding window Fuzzy sets Itemsets constraint Computer science education Time factors
Content Type	Text
Resource Type	Article

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