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Efficient Mining Strategy for Frequent Serial Episodes in Temporal Database

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Frontiers of WWW Research and Development - APWeb 2006 (APWeb 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3841))

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Abstract

Discovering patterns with great significance is an important problem in data mining discipline. A serial episode is defined to be a partially ordered set of events for consecutive and fixed-time intervals in a sequence. Previous studies on serial episodes consider only frequent serial episodes in a sequence of events (called simple sequence). In real world, we may find a set of events at each time slot in terms of various intervals (called complex sequence). Mining frequent serial episodes in complex sequences has more extensive applications than that in simple sequences. In this paper, we discuss the problem on mining frequent serial episodes in a complex sequence. We extend previous algorithm MINEPI to MINEPI+ for serial episode mining from complex sequences. Furthermore, a memory-anchored algorithm called EMMA is introduced for the mining task.

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© 2006 Springer-Verlag Berlin Heidelberg

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Huang, KY., Chang, CH. (2006). Efficient Mining Strategy for Frequent Serial Episodes in Temporal Database. In: Zhou, X., Li, J., Shen, H.T., Kitsuregawa, M., Zhang, Y. (eds) Frontiers of WWW Research and Development - APWeb 2006. APWeb 2006. Lecture Notes in Computer Science, vol 3841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11610113_80

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  • DOI: https://doi.org/10.1007/11610113_80

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-31142-3

  • Online ISBN: 978-3-540-32437-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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