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An Optimal and Progressive Approach to Online Search of Top-K Influential Communities

Summary: Proposes an instance-optimal online search, LocalSearch, for top-k influential communities without indices; runtime scales with the smallest subgraph accessed. Progressive, influence-ordered reporting (no k) and support for other cohesiveness measures; experiments show major speedups over online baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11787
Venue
VLDB
Year
2018
Pagerank
6.3459884e-05
Overall Rank
5,149 | 64.68%
DOI
10.14778/3213880.3213881

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{bi_vldb18,
        title = {{An Optimal and Progressive Approach to Online Search of Top-K Influential Communities}},
        author = {Bi, Fei and Chang, Lijun and Lin, Xuemin and Zhang, Wenjie},
        journal = {PVLDB},
        series = {{VLDB} '18},
        volume = {11},
        number = {9},
        pages = {1056--1068},
        doi = {10.14778/3213880.3213881},
        url = {https://doi.org/10.14778/3213880.3213881},
        year = {2018}
}

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