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An Exemplar-Based Clustering Model with Loose Constraints in Social Network

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Multimedia Technology and Enhanced Learning (ICMTEL 2021)

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Abstract

Loose constraints have great effects on the study of message passing through social networks. This paper proposes a novel EEM-LC model who joints the pairwise loose constraints existing in social networks and the exemplar-based clustering model together, and also observes the application prospects of this model. Exemplar-based clustering model directly selects cluster centers from actual samples, so the structure and semantics of the comments on social networks would be preserved accordingly. Besides, EEM-LC unifies the two pairwise link constraints by one mathematical definition, and looses the restrictions of strong constraints. Moreover, on the basis of the Bayesian probability framework, EEM-LC implants loose pairwise constraints into its target function. That is to say, enhanced \(\alpha \)-expansion move algorithm is capable of optimizing this new model. Experimental results based on several real-world data sets have shown very convincing performance of the proposed EEM-LC model.

Supported by the Humanities and Social Sciences Foundation of the Ministry of Education under grant no.18YJCZH229 and the Natural Science Foundation of Jiangsu Province under grant no. BK20161268.

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Notes

  1. 1.

    http://archive.ics.uci.edu/ml/datasets/Diabetes.

  2. 2.

    http://m.weibo.cn/.

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Authors and Affiliations

  1. Changshu Institute of Technology, Changshu, Jiangsu, China

    Bi Anqi & Ying Wenhao

Authors
  1. Bi Anqi
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  2. Ying Wenhao
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Correspondence to Bi Anqi .

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Editors and Affiliations

  1. Hunan Normal University, Changsha, China

    Weina Fu

  2. University of Jinan, Jinan, China

    Yuan Xu

  3. University of Leicester, Leicester, UK

    Shui-Hua Wang

  4. University of Leicester, Leicester, UK

    Yudong Zhang

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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Anqi, B., Wenhao, Y. (2021). An Exemplar-Based Clustering Model with Loose Constraints in Social Network. In: Fu, W., Xu, Y., Wang, SH., Zhang, Y. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 387. Springer, Cham. https://doi.org/10.1007/978-3-030-82562-1_22

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  • DOI: https://doi.org/10.1007/978-3-030-82562-1_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-82561-4

  • Online ISBN: 978-3-030-82562-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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