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When Engagement Meets Similarity: Efficient (k,r)-Core Computation on Social Networks

Summary: Defines (k,r)-cores combining k-core engagement constraints with pairwise attribute similarity, yielding cohesive social subgraphs. For NP-hard maximal enumeration and maximum-core search, it introduces pruning, search orders, and a novel (k,k′)-core size bound. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11781
Venue
VLDB
Year
2017
Pagerank
6.9619668e-05
Overall Rank
4,008 | 72.51%
DOI
10.14778/3115404.3115412

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Authors

BibTeX Citation

@article{zhang_vldb17,
        title = {{When Engagement Meets Similarity: Efficient (k,r)-Core Computation on Social Networks}},
        author = {Zhang, Fan and Zhang, Ying and Qin, Lu and Zhang, Wenjie and Lin, Xuemin},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {10},
        pages = {998--1009},
        doi = {10.14778/3115404.3115412},
        url = {https://doi.org/10.14778/3115404.3115412},
        year = {2017}
}

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