DBScholar

Back to papers

DMCS : Density Modularity based Community Search

Summary: Introduces Density Modularity, a graph-modularity measure for query-containing community search, the first to leverage modularity in this task. Proposes log-linear algorithms, proves NP-hardness, and shows up to 8.5× NMI gains over baselines on real and synthetic networks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6512
Venue
SIGMOD
Year
2022
Pagerank
6.2001141e-05
Overall Rank
5,491 | 62.33%
DOI
10.1145/3514221.3526137

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{kim_sigmod22,
        title = {{DMCS : Density Modularity based Community Search}},
        author = {Kim, Junghoon and Luo, Siqiang and Cong, Gao and Yu, Wenyuan},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3526137},
        url = {https://dl.acm.org/doi/10.1145/3514221.3526137},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers