Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/2486

 Title: An Algorithm to Mine Normalized Weighted Sequential Patterns Using a Prefix-projected Database Authors: Demetrovics, JanosThi, Vu DucDuong, Tran Huy Keywords: Data MiningFrequent Sequential PatternsWeightedSequential Patterns Issue Date: 2015 Publisher: Institute of Mathematics and Informatics Bulgarian Academy of Sciences Citation: Serdica Journal of Computing, Vol. 9, No 2, (2015), 105p-122p Abstract: Sequential pattern mining is an important subject in data mining with broad applications in many different areas. However, previous sequential mining algorithms mostly aimed to calculate the number of occurrences (the support) without regard to the degree of importance of different data items. In this paper, we propose to explore the search space of subsequences with normalized weights. We are not only interested in the number of occurrences of the sequences (supports of sequences), but also concerned about importance of sequences (weights). When generating subsequence candidates we use both the support and the weight of the candidates while maintaining the downward closure property of these patterns which allows to accelerate the process of candidate generation. URI: http://hdl.handle.net/10525/2486 ISSN: 1312-6555 Appears in Collections: Volume 9 Number 2

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