VGM: Visual Graph Mining

Summary: VGM provides a Java GUI framework for graph classification using graph kernels and SVMs (LIBSVM integrated), lowering the barrier to applying graph-kernel methods. It bundles essential graph mining tools—nearest-neighbor search, shortest paths, product graphs, topological indices—with visualization, enabling rapid experimentation and easy transfer to other SVM backends. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 3869
Venue: SIGMOD
Year: 2006
Pagerank: -
Overall Rank: 13,817 | 5.21%
DOI: 10.1145/1142473.1142570

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Authors

1. Karsten M. Borgwardt (Ludwig Maximilian University of Munich)
2. Sebastian Böttger (Ludwig Maximilian University of Munich)
3. Hans-Peter Kriegel (Ludwig Maximilian University of Munich)

BibTeX Citation

@inproceedings{borgwardt_sigmod06,
        title = {{VGM: Visual Graph Mining}},
        author = {Borgwardt, Karsten M. and Böttger, Sebastian and Kriegel, Hans-Peter},
        series = {{SIGMOD} '06},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1142473.1142570},
        url = {https://dl.acm.org/doi/10.1145/1142473.1142570},
        year = {2006}
}

Incoming Citations (Sorted by Pagerank)

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Rank	Citing Paper	Year	Venue	Pagerank

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Rank	Cited Paper	Year	Venue	Pagerank

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