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PUF-Tree: A Compact Tree Structure for Frequent Pattern Mining of Uncertain Data

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Advances in Knowledge Discovery and Data Mining (PAKDD 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7818))

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Abstract

Many existing algorithms mine frequent patterns from traditional databases of precise data. However, there are situations in which data are uncertain. In recent years, researchers have paid attention to frequent pattern mining from uncertain data. When handling uncertain data, UF-growth and UFP-growth are examples of well-known mining algorithms, which use the UF-tree and the UFP-tree respectively. However, these trees can be large, and thus degrade the mining performance. In this paper, we propose (i) a more compact tree structure to capture uncertain data and (ii) an algorithm for mining all frequent patterns from the tree. Experimental results show that (i) our tree is usually more compact than the UF-tree or UFP-tree, (ii) our tree can be as compact as the FP-tree, and (iii) our mining algorithm finds frequent patterns efficiently.

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Authors and Affiliations

  1. Dept. of Computer Science, University of Manitoba, Canada

    Carson Kai-Sang Leung & Syed Khairuzzaman Tanbeer

Authors
  1. Carson Kai-Sang Leung
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  2. Syed Khairuzzaman Tanbeer
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Editor information

Editors and Affiliations

  1. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada

    Jian Pei

  2. Dept. of Computer Science and Information Engineering, Institute of Medical Informatics, National Cheng Kung University, Tainan, Taiwan

    Vincent S. Tseng

  3. Faculty of Engineering and Information Technology, University of Technology Sydney, Broadway, P.O. Box 123, 2007, Sydney, NSW, Australia

    Longbing Cao  & Guandong Xu  & 

  4. Asian Office of Aerospace Research and Development (AOARD), Air Force Office of Scientific Research (AFOSR), Air Force Research Laboratory USA, Osaka University, 7-23-17 Roppongi, 106-0032, Minato-ku, Tokyo, Japan

    Hiroshi Motoda

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Leung, C.KS., Tanbeer, S.K. (2013). PUF-Tree: A Compact Tree Structure for Frequent Pattern Mining of Uncertain Data. In: Pei, J., Tseng, V.S., Cao, L., Motoda, H., Xu, G. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2013. Lecture Notes in Computer Science(), vol 7818. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37453-1_2

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  • DOI: https://doi.org/10.1007/978-3-642-37453-1_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37452-4

  • Online ISBN: 978-3-642-37453-1

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