GAIA: Graph Classification Using Evolutionary Computation
Summary: GAIA mines discriminative subgraphs for large graphs using a novel encoding and an evolutionary search over pattern space. GAIA produces graph classifiers from mined patterns; outperforms state-of-the-art in accuracy and runtime. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ning Jin (University of North Carolina)
- 2. Calvin Young (University of North Carolina)
- 3. Wei Wang (University of North Carolina)
BibTeX Citation
@inproceedings{jin_sigmod10,
title = {{GAIA: Graph Classification Using Evolutionary Computation}},
author = {Jin, Ning and Young, Calvin and Wang, Wei},
series = {{SIGMOD} '10},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1807167.1807262},
url = {https://dl.acm.org/doi/10.1145/1807167.1807262},
year = {2010}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,631 | Updating Graph Indices with a One-Pass Algorithm | 2015 | SIGMOD | 5.8190404e-05 |
| 8,206 | Mining Top-k Pairs of Correlated Subgraphs in a Large Network | 2020 | VLDB | 5.4666548e-05 |
| 9,207 | Behavior Query Discovery in System-Generated Temporal Graphs | 2016 | VLDB | 5.3058708e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,972 | Mining Significant Graph Patterns by Leap Search | 2008 | SIGMOD | 9.3708222e-05 |
| 4,581 | Mining Graph Patterns Efficiently via Randomized Summaries | 2009 | VLDB | 6.6198548e-05 |
| 5,603 | Output Space Sampling for Graph Patterns | 2009 | VLDB | 6.153476e-05 |
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