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Scalable Technique to Discover Items Support from Trie Data Structure

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Information Computing and Applications (ICICA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7473))

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Abstract

One of the popular and compact trie data structure to represent frequent patterns is via frequent pattern tree (FP-Tree). There are two scanning processes involved in the original database before the FP-Tree can be constructed. One of them is to determine the items support (items and their support) that fulfill minimum support threshold by scanning the entire database. However, if the changes are suddenly occurred in the database, this process must be repeated all over again. In this paper, we introduce a technique called Fast Determination of Item Support Technique (F-DIST) to capture the items support from our proposed Disorder Support Trie Itemset (DOSTrieIT) data structure. Experiments through three UCI benchmark datasets show that the computational time to capture the items support using F-DIST from DOSTrieIT is significantly outperformed the classical FP-Tree technique about 3 orders of magnitude, thus verify its scalability.

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Author information

Authors and Affiliations

  1. Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang Lebuhraya Tun Razak, 26300, Kuantan, Pahang, Malaysia

    A. Noraziah & Tutut Herawan

  2. Department of Computer Science, Universiti Malaysia Terengganu, 21030, Kuala, Terengganu, Malaysia

    Zailani Abdullah

  3. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, 86400, Johor, Malaysia

    Mustafa Mat Deris

Authors
  1. A. Noraziah
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  2. Zailani Abdullah
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  3. Tutut Herawan
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  4. Mustafa Mat Deris
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Editor information

Editors and Affiliations

  1. College of Science, Hebei United University, 063000, Tangshan, Hebei, China

    Baoxiang Liu

  2. Nanyang Technological University, Singapore

    Maode Ma

  3. College of Science, Hebei United University, 063009, Tangshan, Hebei, China

    Jincai Chang

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Noraziah, A., Abdullah, Z., Herawan, T., Deris, M.M. (2012). Scalable Technique to Discover Items Support from Trie Data Structure. In: Liu, B., Ma, M., Chang, J. (eds) Information Computing and Applications. ICICA 2012. Lecture Notes in Computer Science, vol 7473. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34062-8_65

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  • DOI: https://doi.org/10.1007/978-3-642-34062-8_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34061-1

  • Online ISBN: 978-3-642-34062-8

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