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SCAN++: Efficient Algorithm for Finding Clusters, Hubs and Outliers on Large-scale Graphs

Summary: SCAN++ accelerates SCAN’s joint discovery of clusters, hubs, and outliers in large graphs using DTAR, a two-hop reachability structure that prunes and shares density evaluations. It preserves SCAN’s exact results while substantially reducing runtime. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11185
Venue
VLDB
Year
2015
Pagerank
8.066541e-05
Overall Rank
2,839 | 80.53%
DOI
10.14778/2809974.2809980

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{shiokawa_vldb15,
        title = {{SCAN++: Efficient Algorithm for Finding Clusters, Hubs and Outliers on Large-scale Graphs}},
        author = {Shiokawa, Hiroaki and Fujiwara, Yasuhiro and Onizuka, Makoto},
        journal = {PVLDB},
        series = {{VLDB} '15},
        volume = {8},
        number = {11},
        doi = {10.14778/2809974.2809980},
        url = {https://doi.org/10.14778/2809974.2809980},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

Rank Cited Paper Year Venue Pagerank
3 Pregel: A System for Large-Scale Graph Processing 2010 SIGMOD 0.0012250108
102 Truss Decomposition in Massive Networks 2012 VLDB 0.00034255289
262 On Triangulation-based Dense Neighborhood Graph Discovery 2011 VLDB 0.00023084332
12,153 Scaling Manifold Ranking Based Image Retrieval 2015 VLDB 5.093636e-05
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