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Querying historical K-cores in large temporal graphs

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Abstract

Many real-world relationships between entities can be modeled as temporal graphs, where each edge is associated with a timestamp or a time interval representing its occurrence. The k-core is a fundamental model used to capture cohesive subgraphs in a simple graph and have drawn much research attention over the last decade. Despite widespread research, none of the existing works support the efficient querying of historical k-cores in temporal graphs. In this paper, given an integer k and a time window, we study the problem of computing all the nodes belonging to the k-core in the graph snapshot over the time window. We propose an index-based solution and several pruning strategies to reduce the index size. We design a novel algorithm to construct this index, whose running time is linear to the final index size. We also propose algorithms to maintain our index given the continuous arrival of new edges. Lastly, we conducted extensive experiments on several real-world temporal graphs to show the high effectiveness of our index-based solution.

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Notes

  1. https://github.com/yuyuanhang/Historical-K-Cores-Query.

  2. http://snap.stanford.edu/.

  3. http://konect.cc/.

  4. https://networkrepository.com/index.php.

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Funding

Dong Wen is supported by ARC DP230-101445 and ARC DE240100668. Lu Qin is supported by ARC FT200100787 and ARC DP240101322. Wenjie Zhang is supported by ARC DP230101445 and ARC FT210100303. Xuemin Lin is supported by NSFC U2241211 and NSFC U20B2046.

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Authors and Affiliations

  1. AAII, University of Technology Sydney, Ultimo, Australia

    Yuanhang Yu & Lu Qin

  2. The University of New South Wales, Sydney, Australia

    Dong Wen & Wenjie Zhang

  3. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Sha Tin, China

    Michael Yu

  4. School of Computer Science and Information Technology and School of Statistics & Mathematics, Zhejiang Gongshang University, Hangzhou, China

    Ying Zhang

  5. Shanghai Jiao Tong University, Shanghai, China

    Xuemin Lin

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  1. Yuanhang Yu
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Correspondence to Ying Zhang.

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Yu, Y., Wen, D., Yu, M. et al. Querying historical K-cores in large temporal graphs. The VLDB Journal 34, 26 (2025). https://doi.org/10.1007/s00778-025-00903-1

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