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Approximate Pattern Matching in Massive Graphs with Precision and Recall Guarantees

Summary: Novel optimization opportunities enable a scalable pipeline for approximate graph pattern matching with 100% precision and recall for k-edit-distance subgraphs of a template. It fuses edit-distance matching with pruning, supports arbitrary patterns, and scales to graphs with hundreds of billions to trillions of edges. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5779
Venue
SIGMOD
Year
2020
Pagerank
4.1945683e-05
Overall Rank
11,559 | 19.59%
DOI
10.1145/3318464.3380566

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