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OLAK: An Efficient Algorithm to Prevent Unraveling in Social Networks

Summary: OLAK uses an onion-layer (onion-peeling) structure to solve anchored k-core on large graphs, constraining anchors to onion layers and enabling aggressive pruning. Experiments on 10 real networks show scalable, efficient performance on general graphs, outperforming bounded-treewidth methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h2c95faf48af121fd
Venue
VLDB
Year
2017
Pagerank
6.5226071e-05
Overall Rank
4,578 | 69.23%
DOI
10.14778/3055330.3055336

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhang_vldb17,
        title = {{OLAK: An Efficient Algorithm to Prevent Unraveling in Social Networks}},
        author = {Zhang, Fan and Zhang, Wenjie and Zhang, Ying and Qin, Lu and Lin, Xuemin},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {6},
        pages = {649--660},
        doi = {10.14778/3055330.3055336},
        url = {https://doi.org/10.14778/3055330.3055336},
        year = {2017}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
285 Local Search of Communities in Large Graphs 2014 SIGMOD 0.00022150572
589 Large Scale Cohesive Subgraphs Discovery for Social Network Visual Analysis 2013 VLDB 0.00015905948
758 Streaming Algorithms for k-core Decomposition 2013 VLDB 0.00014188163
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