Cohesive Subgraph Search over Big Heterogeneous Information Networks: Applications, Challenges, and Solutions
Summary: Tutorial survey of cohesive subgraph search in heterogeneous information networks (HINs), focusing on models, algorithms, and scalable techniques. Covers applications (community search, recommendations, fraud detection), reviews methods, compares approaches, and outlines open challenges and future directions. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yixiang Fang (Chinese University of Hong Kong)
- 2. Kai Wang (University of New South Wales)
- 3. Xuemin Lin (University of New South Wales)
- 4. Wenjie Zhang (University of New South Wales)
BibTeX Citation
@inproceedings{fang_sigmod21,
title = {{Cohesive Subgraph Search over Big Heterogeneous Information Networks: Applications, Challenges, and Solutions}},
author = {Fang, Yixiang and Wang, Kai and Lin, Xuemin and Zhang, Wenjie},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3457538},
url = {https://dl.acm.org/doi/10.1145/3448016.3457538},
year = {2021}
}
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