Inductive Attributed Community Search: to Learn Communities across Graphs
Summary: IACS: an inductive encoder–decoder framework for attributed community search that learns a shared prior across tasks to generalize to unseen, heterogeneous graphs. Training–adaptation–inference enables few-shot adaptation to new graphs, yielding ~29%/25.6% F1 gains over transductive baselines. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Shuheng Fang
- 2. Kangfei Zhao
- 3. Yu Rong
- 4. Zhixun Li
- 5. Jeffrey Xu Yu
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,648 | A Comprehensive Survey and Experimental Study of Learning-based Community Search | 2025 | VLDB | 4.1945683e-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 |
|---|---|---|---|---|
| 999 | Effective Community Search for Large Attributed Graphs | 2016 | VLDB | 0.00014726563 |
| 1,550 | Approximate Closest Community Search in Networks | 2016 | VLDB | 0.00011423628 |
| 1,645 | Attribute-Driven Community Search | 2017 | VLDB | 0.00011037459 |
| 2,897 | ICS-GNN: Lightweight Interactive Community Search via Graph Neural Network | 2021 | VLDB | 7.9450406e-05 |
| 3,001 | Neural Subgraph Counting with Wasserstein Estimator | 2022 | SIGMOD | 7.7404487e-05 |
| 3,369 | Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed | 2022 | VLDB | 7.171452e-05 |
| 3,778 | A Learned Sketch for Subgraph Counting | 2021 | SIGMOD | 6.7747398e-05 |
| 5,521 | Efficient Streaming Subgraph Isomorphism with Graph Neural Networks | 2021 | VLDB | 5.4614637e-05 |
| 7,409 | CommunityAF: An Example-based Community Search Method via Autoregressive Flow | 2023 | VLDB | 4.7370979e-05 |
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