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Group homophily based facility location selection in geo-social networks

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Abstract

Conditional p-center problem is one of the classical facility location problems, which aims to find p facilities meeting the given distance condition with q pre-existing facilities. It is worth noting that, with the proliferation of the social network, the effect of social factor is non-negligible. However, the state-of-the-art solutions for the conditional p-center problem fail to deal with the social-aware scenario, and the key challenge is that the existing methods are incompatible with integrating the social condition. In this paper, we first formalize the conditional p-center problem in geo-social networks (GSCpC). To tackle this problem, we develop a homophily-based relaxation algorithm by considering both social constraint and spatial constraint. Specifically, in the first phase, we propose a partition algorithm based on Voronoi diagram to conquer the social constraint. Next, in the second phase, we propose a heuristic algorithm to refine the query results by minimizing the distance. To accelerate the performance, we also propose a category-aware user grouping strategy and a spatial distance based strategy to prune the unpromising results significantly. Experimental results on real-world datasets demonstrate that our approaches are more efficient and effective compared to the benchmarks.

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Notes

  1. Homophily is a group concept that reflects the preference of the users in a group. Assigning the users with a higher homophily score to the same facility will progress connected people more similar.

  2. http://snap.stanford.edu/data/index.html

  3. https://developer.foursquare.com/

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Acknowledgements

The work is partially supported by the National Nature Science Foundation of China (No. 62002054), Industry-university-research Innovation Fund for Chinese Universities (No. 2020ITA03009), China Postdoctoral Science Foundation (No. 2020M67 0780), and Postdoctoral Research Foundation of Northeast University.

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Authors and Affiliations

  1. School of Business Administration, Northeastern University, Shenyang, China

    Yuliang Ma & Zhong-Zhong Jiang

  2. School of Computer Science and Technology, Anhui University, Hefei, China

    Ningning Cui

  3. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

    Ye Yuan & Guoren Wang

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  1. Yuliang Ma
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Correspondence to Ningning Cui.

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This article belongs to the Topical Collection: Special Issue on Decision Making in Heterogeneous Network Data Scenarios and Applications

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Ma, Y., Cui, N., Jiang, ZZ. et al. Group homophily based facility location selection in geo-social networks. World Wide Web 26, 33–53 (2023). https://doi.org/10.1007/s11280-022-01008-3

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