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Pacific-Asia Conference on Knowledge Discovery and Data Mining

PAKDD 2017: Trends and Applications in Knowledge Discovery and Data Mining pp 79–93Cite as

Improved CFDP Algorithms Based on Shared Nearest Neighbors and Transitive Closure

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10526))

Abstract

A recently proposed clustering algorithm named Clustering by fast search and Find of Density Peaks (CFDP) can automatically identify the cluster centers without an iterative process. The key step in CFDP is searching for the nearest neighbor with higher density for each point. However, the CFDP algorithm may not be effective for cases in which there exist density fluctuations within a cluster or between two nearby clusters. In this study, two improved algorithms named CFDP-ED-TSNN1 and CFDP-ED-TSNN2 are presented, which adopt different ways to utilize the dissimilarity. Here, the dissimilarity is based on shared nearest neighbors and transitive closure. The experimental results on both several artificial datasets and a real-world dataset show that the improved algorithms are competitive.

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Acknowledgements

This work is partly supported by the Anhui Provincial Natural Science Foundation (No. 1408085MKL07).

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Authors and Affiliations

  1. Anhui Province Key Laboratory of Software Engineering in Computing and Communication, School of Computer Science and Technology, University of Science and Technology of China, Hefei, 230027, Anhui, China

    Li Ni, Wenjian Luo, Chenyang Bu & Yamin Hu

Authors
  1. Li Ni
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  2. Wenjian Luo
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  3. Chenyang Bu
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  4. Yamin Hu
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Corresponding author

Correspondence to Wenjian Luo .

Editor information

Editors and Affiliations

  1. Seoul National University, Seoul, Korea (Republic of)

    U Kang

  2. School of Information Systems, Singapore Management University, Singapore, Singapore

    Ee-Peng Lim

  3. Chinese University of Hong Kong, Hong Kong, China

    Jeffrey Xu Yu

  4. Kangwon National University, Chuncheon, Korea (Republic of)

    Yang-Sae Moon

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Ni, L., Luo, W., Bu, C., Hu, Y. (2017). Improved CFDP Algorithms Based on Shared Nearest Neighbors and Transitive Closure. In: Kang, U., Lim, EP., Yu, J., Moon, YS. (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2017. Lecture Notes in Computer Science(), vol 10526. Springer, Cham. https://doi.org/10.1007/978-3-319-67274-8_8

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  • DOI: https://doi.org/10.1007/978-3-319-67274-8_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67273-1

  • Online ISBN: 978-3-319-67274-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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