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Toward maintenance of hypercores in large-scale dynamic hypergraphs

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Abstract

In this paper, we study hypercore maintenance in large-scale dynamic hypergraphs. A hypergraph, whose hyperedges may contain a set of vertices rather than two vertices in pairwise graphs, can represent complex interactions in more sophisticated applications. However, the exponential number of hyperedges incurs unaffordable costs to recompute the hypercore number of vertices and hyperedges when updating a hypergraph. This motivates us to propose an efficient approach for exact hypercore maintenance with the intention of significantly reducing the hypercore updating time comparing with recomputation approaches. The proposed algorithms can pinpoint the vertices and hyperedges whose hypercore numbers have to be updated by only traversing a small sub-hypergraph. We also propose an index called Core-Index that can facilitate our maintenance algorithms. Extensive experiments on real-world and temporal hypergraphs demonstrate the superiority of our algorithms in terms of efficiency.

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  1. https://www.cs.cornell.edu/arb/data/.

  2. https://skubuntu.com.

  3. https://dblp.uni-trier.de/.

  4. https://stackoverflow.com.

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Acknowledgements

This work was supported in part by the National Key Research and Development Program of China under Grant 2020YFB1005900, in part by National Natural Science Foundation of China (NSFC) under Grant 62122042, and in part by Shandong University multidisciplinary research and innovation team of young scholars under Grant 2020QNQT017. Dongxiao Yu is the corresponding author of this work.

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Authors and Affiliations

  1. School of Computer Science and Technology, Shandong University, Qingdao, People’s Republic of China

    Qi Luo, Dongxiao Yu & Xiuzhen Cheng

  2. Department of Computing Science, Georgia State University, Atlanta, USA

    Zhipeng Cai

  3. School of Computer Science and Engineering, University of New South Wales, Sydney, Australia

    Xuemin Lin

  4. School of Mathematics, Shandong University, Jinan, People’s Republic of China

    Guanghui Wang

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Luo, Q., Yu, D., Cai, Z. et al. Toward maintenance of hypercores in large-scale dynamic hypergraphs. The VLDB Journal 32, 647–664 (2023). https://doi.org/10.1007/s00778-022-00763-z

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