DBScholar

Back to papers

A Particle-and-Density Based Evolutionary Clustering Method for Dynamic Networks

Summary: Particle-and-density evolutionary clustering for dynamic networks; nano-communities and quasi l-KK cliques support variable forming/dissolving communities. Information-theoretic mapping to quasi l-KK with cost embedding yields temporally smoothed, data-aligned clusters and stage detection (evolving/forming/dissolving) with 10x speedups. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10082
Venue
VLDB
Year
2009
Pagerank
6.3192921e-05
Overall Rank
5,203 | 64.31%
DOI
10.14778/1687627.1687698

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{kim_vldb09,
        title = {{A Particle-and-Density Based Evolutionary Clustering Method for Dynamic Networks}},
        author = {Kim, Min-Soo and Han, Jiawei},
        journal = {PVLDB},
        series = {{VLDB} '09},
        doi = {10.14778/1687627.1687698},
        url = {https://doi.org/10.14778/1687627.1687698},
        year = {2009}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Previous Page 1 / 1 Next

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.

Previous Page 1 / 1 Next

Semantically Similar Papers