Graph Clustering Based on Structural/Attribute Similarities
Summary: SA-Cluster jointly clusters attributed-graph vertices using a unified structural/attribute distance, seeking dense and attribute-homogeneous groups. It automatically learns the relative weight of topology versus heterogeneous attributes and provides convergence guarantees. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yang Zhou (Chinese University of Hong Kong)
- 2. Hong Cheng (Chinese University of Hong Kong)
- 3. Jeffrey Xu Yu (Chinese University of Hong Kong)
BibTeX Citation
@article{zhou_vldb09,
title = {{Graph Clustering Based on Structural/Attribute Similarities}},
author = {Zhou, Yang and Cheng, Hong and Yu, Jeffrey Xu},
journal = {PVLDB},
series = {{VLDB} '09},
volume = {2},
number = {1},
pages = {25--36},
doi = {10.14778/1687627.1687631},
url = {https://doi.org/10.14778/1687627.1687631},
year = {2009}
}
Incoming Citations (Sorted by Pagerank)
Showing 33 of 33 citing papers.
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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 |
|---|---|---|---|---|
| 94 | Efficient and Effective Clustering Methods for Spatial Data Mining | 1994 | VLDB | 0.00034579889 |
| 308 | Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications | 1998 | SIGMOD | 0.00021473921 |
| 497 | Efficient Aggregation for Graph Summarization | 2008 | SIGMOD | 0.00017318153 |
| 563 | Graph Summarization with Bounded Error | 2008 | SIGMOD | 0.00016327158 |
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