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Hierarchical high-order co-clustering algorithm by maximizing modularity

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Abstract

The star-structured high-order heterogeneous data is ubiquitous, such data represent objects of a certain type, connected to other types of data, or the features, so that the overall data schema forms a star-structure of inter-relationships. In this paper, we study the problem of co-clustering of star-structured high-order heterogeneous data. We present a new solution, a Hierarchical High-order Co-clustering Algorithm by Maximizing Modularity, MHCoC, which iteratively optimizes the objective function based on modularity and finally converges to a unique clustering result. In contrast to the traditional co-clustering methods, MHCoC merges information of multiple feature spaces of high-order heterogeneous data. Moreover, MHCoC takes a top-down strategy to perform a greedy divisive procedure, generating a tree-like hierarchical clustering result that reveal the relationship between clusters. To illustrate the process in more detail, we design a toy example to describe how MHCoC selects the appropriate co-cluster and splits it. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed method.

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Acknowledgements

The work is supported by the National Natural Science Foundation of China (No.61762078, 61363058, 61762079), Guangxi Key Laboratory of Trusted Software (No. kx201910) and Research Fund of Guangxi Key Lab of Multi-source Information Mining & Security (MIMS18-08)

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Authors and Affiliations

  1. College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, Gansu, China

    Jiahui Wei, Huifang Ma & Yuhang Liu

  2. Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin, 541004, Guangxi, China

    Huifang Ma

  3. Guangxi Key Lab of Multi-Source Information Mining and Security, Guangxi Normal University, Guilin, 541004, Guangxi, China

    Huifang Ma & Zhixin Li

  4. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China

    Ning Li

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  1. Jiahui Wei
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  2. Huifang Ma
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  3. Yuhang Liu
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  5. Ning Li
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Correspondence to Huifang Ma.

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Wei, J., Ma, H., Liu, Y. et al. Hierarchical high-order co-clustering algorithm by maximizing modularity. Int. J. Mach. Learn. & Cyber. 12, 2887–2898 (2021). https://doi.org/10.1007/s13042-021-01375-9

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  • DOI: https://doi.org/10.1007/s13042-021-01375-9

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