Effective and Efficient Community Search over Large Heterogeneous Information Networks
Summary: Community search over large heterogeneous information networks (HINs) using meta-paths to yield type-consistent dense subgraphs containing the query. Proposes meta-path-augmented minimum-degree cohesiveness and efficient algorithms; experiments on five real HINs show effectiveness and speedups over baselines. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yixiang Fang (University of New South Wales)
- 2. Yixing Yang (University of New South Wales)
- 3. Wenjie Zhang (University of New South Wales)
- 4. Xuemin Lin (University of New South Wales)
- 5. Xin Cao (University of New South Wales)
BibTeX Citation
@article{fang_vldb20,
title = {{Effective and Efficient Community Search over Large Heterogeneous Information Networks}},
author = {Fang, Yixiang and Yang, Yixing and Zhang, Wenjie and Lin, Xuemin and Cao, Xin},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {6},
pages = {854--867},
doi = {10.14778/3380750.3380756},
url = {https://doi.org/10.14778/3380750.3380756},
year = {2020}
}
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