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K-Medoids-Based Consensus Clustering Based on Cell-Like P Systems with Promoters and Inhibitors

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Bio-inspired Computing – Theories and Applications (BIC-TA 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 681))

Abstract

Consensus clustering is a class of robust clustering algorithms, which obtain the finally clustering results based on multiple existing basic partitionings. In this study, we introduce the K-medoids algorithm and the cell-like P systems with promoters and inhibiters (a class of parallel and distributed computing models) to the consensus clustering, and propose the K-medoids-based consensus clustering based on the cell-like P system with promoters and inhibiters. Through the experiment, the proposed consensus clustering algorithm can obtain high quality clustering results in a short time. This study improves the result in TKDE, 2015, 2, 155–169.

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Acknowledgment

This work is supported by the Natural Science Foundation of China (Nos. 61170038, 61472231, 61402187, 61502535, 61572522 and 61572523).

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Authors and Affiliations

  1. School of Management Science and Engineering, Shandong Normal University, Jinan, 250014, China

    Xiyu Liu, Yuzhen Zhao & Wenxing Sun

Authors
  1. Xiyu Liu
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  2. Yuzhen Zhao
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  3. Wenxing Sun
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Corresponding author

Correspondence to Yuzhen Zhao .

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Editors and Affiliations

  1. Xidian University, Xi’an, China

    Maoguo Gong

  2. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  3. China University of Petroleum, Qingdao, China

    Tao Song

  4. Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak Campus, Kuching, China

    Gexiang Zhang

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Liu, X., Zhao, Y., Sun, W. (2016). K-Medoids-Based Consensus Clustering Based on Cell-Like P Systems with Promoters and Inhibitors. In: Gong, M., Pan, L., Song, T., Zhang, G. (eds) Bio-inspired Computing – Theories and Applications. BIC-TA 2016. Communications in Computer and Information Science, vol 681. Springer, Singapore. https://doi.org/10.1007/978-981-10-3611-8_11

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  • DOI: https://doi.org/10.1007/978-981-10-3611-8_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3610-1

  • Online ISBN: 978-981-10-3611-8

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