Inductive Attributed Community Search: to Learn Communities across Graphs
Summary: IACS reframes attributed community search as inductive task learning, using an encoder–decoder and training–adaptation–inference workflow to transfer knowledge across heterogeneous graphs and queries. Few-shot adaptation yields 29.0% CS and 25.6% ACS average F1 gains. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Shuheng Fang (Chinese University of Hong Kong)
- 2. Kangfei Zhao (Beijing Institute of Technology)
- 3. Yu Rong (Alibaba)
- 4. Zhixun Li (Chinese University of Hong Kong)
- 5. Jeffrey Xu Yu (Chinese University of Hong Kong)
BibTeX Citation
@article{fang_vldb24,
title = {{Inductive Attributed Community Search: to Learn Communities across Graphs}},
author = {Fang, Shuheng and Zhao, Kangfei and Rong, Yu and Li, Zhixun and Yu, Jeffrey Xu},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {10},
pages = {2576--2589},
doi = {10.14778/3675034.3675048},
url = {https://doi.org/10.14778/3675034.3675048},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,900 | A Comprehensive Survey and Experimental Study of Learning-based Community Search | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 706 | Effective Community Search for Large Attributed Graphs | 2016 | VLDB | 0.00014789612 |
| 1,113 | Approximate Closest Community Search in Networks | 2016 | VLDB | 0.00012124571 |
| 1,239 | Attribute-Driven Community Search | 2017 | VLDB | 0.000115381 |
| 2,383 | ICS-GNN: Lightweight Interactive Community Search via Graph Neural Network | 2021 | VLDB | 8.6527736e-05 |
| 2,731 | Neural Subgraph Counting with Wasserstein Estimator | 2022 | SIGMOD | 8.1959181e-05 |
| 2,873 | Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed | 2022 | VLDB | 8.0099557e-05 |
| 3,283 | A Learned Sketch for Subgraph Counting | 2021 | SIGMOD | 7.56675e-05 |
| 5,118 | Efficient Streaming Subgraph Isomorphism with Graph Neural Networks | 2021 | VLDB | 6.3580186e-05 |
| 7,391 | CommunityAF: An Example-based Community Search Method via Autoregressive Flow | 2023 | VLDB | 5.626608e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 8,821 | Efficient Unsupervised Community Search with Pre-trained Graph Transformer | 2024 | VLDB |
| 2 | 9,690 | Searching and Detecting Structurally Similar Communities in Large Heterogeneous Information Networks | 2025 | VLDB |
| 3 | 706 | Effective Community Search for Large Attributed Graphs | 2016 | VLDB |
| 4 | 8,477 | Cohesiveness-aware Hierarchical Compressed Index for Community Search on Attributed Graphs | 2025 | SIGMOD |
| 5 | 5,877 | Neural Attributed Community Search at Billion Scale | 2023 | SIGMOD |
| 6 | 9,691 | A Flexible Framework for Query-oriented Interactive Community Search | 2025 | VLDB |
| 7 | 2,383 | ICS-GNN: Lightweight Interactive Community Search via Graph Neural Network | 2021 | VLDB |
| 8 | 9,688 | Deep Overlapping Community Search via Subspace Embedding | 2025 | SIGMOD |
| 9 | 10,900 | A Comprehensive Survey and Experimental Study of Learning-based Community Search | 2025 | VLDB |
| 10 | 2,873 | Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed | 2022 | VLDB |