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Community search over heterogeneous information networks via weighting strategy and query replacement

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This paper studies the problem of community search,which aims to search a community for a query vertex in an HIN. Specifically, we design a weighting strategy and query node replacement for the community search problem on heterogeneous networks. The weighting strategy enables the induced homogeneous graph to contain more semantic information; the query node replacement strategy can find better quality nodes for community search. We conduct extensive experiments on real-world graphs to show that our proposed methods can provide high-quality results over HINs.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61762078, 61363058, 61966004), Natural Science Foundation of Gansu (21JR7RA114), and Northwest Normal University Young Teachers Research Capacity Promotion Plan (NWNU-LKQN2019-2).

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Authors and Affiliations

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

    Fanyi Yang, Huifang Ma & Weiwei Gao

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

    Huifang Ma & Zhixin Li

Authors
  1. Fanyi Yang
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  2. Huifang Ma
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  3. Weiwei Gao
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  4. Zhixin Li
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Corresponding author

Correspondence to Huifang Ma.

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The supporting information is available online at journal.hep.com.cn and link.springer.com.

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Yang, F., Ma, H., Gao, W. et al. Community search over heterogeneous information networks via weighting strategy and query replacement. Front. Comput. Sci. 16, 164345 (2022). https://doi.org/10.1007/s11704-022-1329-9

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  • DOI: https://doi.org/10.1007/s11704-022-1329-9

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