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Effective Database Transformation and Efficient Support Computation for Mining Sequential Patterns

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Database Systems for Advanced Applications (DASFAA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3453))

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Abstract

In this paper, we introduce a novel algorithm for mining sequential patterns from transaction databases. Since the FP-tree based approach is efficient in mining frequent itemsets, we adapt it to find frequent 1-sequences. For efficient frequent k-sequence mining, every frequent 1-sequence is encoded as a unique symbol and the database is transformed into one in the symbolic form. We observe that it is unnecessary to encode all the frequent 1-seqences, and make full use of the discovered frequent 1-sequences to transform the database into one with a smallest size. To discover the frequent k-sequences, we design a tree structure to store the candidates. Each customer sequence is then scanned to decide whether the candidates are frequent k-sequences. We propose a technique to avoid redundantly enumerating the identical k-subsequences from a customer sequence to speed up the process. Moreover, the tree structure is designed in a way such that the supports of the candidates can be incremented for a customer sequence by a single sequential traversal of the tree. The experiment results show that our approach outperforms the previous works in various aspects including the scalability and the execution time.

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© 2005 Springer-Verlag Berlin Heidelberg

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Cho, CW., Wu, YH., Chen, A.L.P. (2005). Effective Database Transformation and Efficient Support Computation for Mining Sequential Patterns. In: Zhou, L., Ooi, B.C., Meng, X. (eds) Database Systems for Advanced Applications. DASFAA 2005. Lecture Notes in Computer Science, vol 3453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11408079_16

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  • DOI: https://doi.org/10.1007/11408079_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25334-1

  • Online ISBN: 978-3-540-32005-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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