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A biased edge enhancement method for truss-based community search

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Conclusion

Most truss-based community search methods are usually confronted with the fragmentation issue. We propose a Biased edge Enhancement method for Truss-based Community Search (BETCS) to address the issue. This paper mainly solves the fragmentation problem in truss community query through data enhancement. In future work, we will consider applying the methods in the text to directed graphs or dynamic graphs.

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Acknowledgements

This work was supported by the Research Foundation of Education Bureau of Hunan Province of China (Grant Nos. 20B625, 22B0275), and the Changsha Natural Science Foundation (Grant No. kq2202294).

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Authors and Affiliations

  1. School of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha, 410082, China

    Yuqi Li & Tao Meng

  2. School of Business, Central South University of Forestry and Technology, Changsha, 410082, China

    Zhixiong He

  3. College of Information Engineering, Changsha Medical University, Changsha, 410219, China

    Haiyan Liu

  4. Department of Computer Science, State University of New York, New York, 12561, USA

    Keqin Li

Authors
  1. Yuqi Li
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  2. Tao Meng
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  3. Zhixiong He
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  4. Haiyan Liu
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  5. Keqin Li
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Corresponding author

Correspondence to Tao Meng.

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Competing interests The authors declare that they have no competing interests or financial conflicts to disclose.

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Electronic supplementary material Supplementary material is available in the online version of this article at http://www.journal.hep.com.cn and http://www.link.springer.com

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Li, Y., Meng, T., He, Z. et al. A biased edge enhancement method for truss-based community search. Front. Comput. Sci. 18, 183610 (2024). https://doi.org/10.1007/s11704-024-2604-8

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  • DOI: https://doi.org/10.1007/s11704-024-2604-8

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