Neural Attributed Community Search at Billion Scale
Summary: Neural attributed community search for billion-scale graphs. ALICE combines density sketch modularity to extract modular k-hop subgraph and a cross-attention ConNet on a node-attr graph to predict communities under structure-attr and local consistency. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Jianwei Wang (University of New South Wales)
- 2. Kai Wang (Shanghai Jiao Tong University)
- 3. Xuemin Lin (Shanghai Jiao Tong University)
- 4. Wenjie Zhang (University of New South Wales)
- 5. Ying Zhang (University of Technology Sydney)
BibTeX Citation
@inproceedings{wang_sigmod23,
title = {{Neural Attributed Community Search at Billion Scale}},
author = {Wang, Jianwei and Wang, Kai and Lin, Xuemin and Zhang, Wenjie and Zhang, Ying},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3626738},
url = {https://dl.acm.org/doi/10.1145/3626738},
year = {2023}
}
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