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iCHUM: An Efficient Algorithm for High Utility Mining in Incremental Databases

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Knowledge Science, Engineering and Management (KSEM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9403))

Abstract

High utility mining is a fundamental topic in association rule mining, which aims to discover all itemsets with high utility from transaction database. The previous studies are mainly based on fixed databases, which are not applicable for incremental databases. Although incremental high utility pattern (IHUP) mining has been proposed, its tree structure IHUP-Tree is redundant and thus IHUP algorithm has relative low efficiency. To address this issue, we propose an incremental compressed high utility mining algorithm called iCHUM. The iCHUM algorithm utilizes items of high transaction weighted utilization (TWU) to construct its tree structure, namely iCHUM-Tree. The iCHUM algorithm updates iCHUM-Tree when new database is appended to the original database. The information of high utility itemsets is maintained in the iCHUM-Tree such that candidate itemsets can be generated through mining procedure. Performance analysis shows that our algorithm is more efficient than baseline approaches in incremental databases.

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Author information

Authors and Affiliations

  1. Tsinghua-Southampton Web Science Laboratory, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China

    Hai-Tao Zheng & Zhuo Li

Authors
  1. Hai-Tao Zheng
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  2. Zhuo Li
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Correspondence to Hai-Tao Zheng .

Editor information

Editors and Affiliations

  1. Chinese Academy of Sciences, Beijing, China

    Songmao Zhang

  2. Ludwig-Maximilians-Universität München, Munich, Germany

    Martin Wirsing

  3. Southwest University, Chongqing, China

    Zili Zhang

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© 2015 Springer International Publishing Switzerland

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Zheng, HT., Li, Z. (2015). iCHUM: An Efficient Algorithm for High Utility Mining in Incremental Databases. In: Zhang, S., Wirsing, M., Zhang, Z. (eds) Knowledge Science, Engineering and Management. KSEM 2015. Lecture Notes in Computer Science(), vol 9403. Springer, Cham. https://doi.org/10.1007/978-3-319-25159-2_20

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  • DOI: https://doi.org/10.1007/978-3-319-25159-2_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25158-5

  • Online ISBN: 978-3-319-25159-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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