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An Improved CURE Algorithm

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Intelligence Science II (ICIS 2018)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 539))

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Abstract

CURE algorithm is an efficient hierarchical clustering algorithm for large data sets. This paper presents an improved CURE algorithm, named ISE-RS-CURE. The algorithm adopts a sample extraction algorithm combined with statistical ideas, which can reasonably select sample points according to different data densities and can improve the representation of sample sets. When the sample set is extracted, the data set is divided at the same time, which can help to reduce the time consumption in the non-sample set allocation process. A selection strategy based on partition influence factor is proposed for the selection of representative points, which comprehensively considers the overall correlation between the data in the region where a representative point is located, so as to improve the rationality of the representative points. Experiments show that the improved CURE algorithm proposed in this paper can ensure the accuracy of the clustering results and can also improve the operating efficiency.

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Author information

Authors and Affiliations

  1. College of Computer Science and Engineering, Shandong Province Key Laboratory of Wisdom Mine Information Technology, Shandong University of Science and Technology, Qingdao, 266590, China

    Mingjuan Cai

  2. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China

    Yongquan Liang

Authors
  1. Mingjuan Cai
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  2. Yongquan Liang
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Corresponding author

Correspondence to Yongquan Liang .

Editor information

Editors and Affiliations

  1. Chinese Academy of Sciences, Beijing, China

    Zhongzhi Shi

  2. University of Amsterdam, Amsterdam, The Netherlands

    Cyriel Pennartz

  3. Peking University, Beijing, China

    Tiejun Huang

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© 2018 IFIP International Federation for Information Processing

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Cai, M., Liang, Y. (2018). An Improved CURE Algorithm. In: Shi, Z., Pennartz, C., Huang, T. (eds) Intelligence Science II. ICIS 2018. IFIP Advances in Information and Communication Technology, vol 539. Springer, Cham. https://doi.org/10.1007/978-3-030-01313-4_11

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  • DOI: https://doi.org/10.1007/978-3-030-01313-4_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01312-7

  • Online ISBN: 978-3-030-01313-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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