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)

Paper ID: h7b5ae9573959520c
Venue: SIGMOD
Year: 2010
Pagerank: 5.6860134e-05
Overall Rank: 6,773 | 54.47%
DOI: 10.1145/1807167.1807262

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
6,760	Updating Graph Indices with a One-Pass Algorithm	2015	SIGMOD	5.6887265e-05
8,342	Mining Top-k Pairs of Correlated Subgraphs in a Large Network	2020	VLDB	5.3516819e-05
9,386	Behavior Query Discovery in System-Generated Temporal Graphs	2016	VLDB	5.1868213e-05

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
2,010	Mining Significant Graph Patterns by Leap Search	2008	SIGMOD	9.1914756e-05
4,647	Mining Graph Patterns Efficiently via Randomized Summaries	2009	VLDB	6.4867875e-05
5,729	Output Space Sampling for Graph Patterns	2009	VLDB	6.0157118e-05

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