cgSpan: Closed Graph-Based Substructure Pattern Mining
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Abstract (arXiv)
gSpan is a popular algorithm for mining frequent subgraphs. cgSpan (closed graph-based substructure pattern mining) is a gSpan extension that only mines closed subgraphs. A subgraph g is closed in the graphs database if there is no proper frequent supergraph of g that has equivalent occurrence with g. cgSpan adds the Early Termination pruning method to the gSpan pruning methods, while leaving the original gSpan steps unchanged. cgSpan also detects and handles cases in which Early Termination should not be applied. To the best of our knowledge, cgSpan is the first publicly available implementation for closed graphs mining
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 0 of its 14 references that are in the map. First posted on arXiv 17 Dec 2021.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 1; 2025: 1.
5 papers.
- 2023Pattern Mining for Anomaly Detection in Graphs: Application to Fraud in Public Procurementcited by 2
- 2022MDL-based Compressing Sequential Rulescited by 1
- 2024In-Context Learning of Physical Properties: Few-Shot Adaptation to Out-of-Distribution Molecular Graphscited by 1
- 2023Farspredict: A benchmark dataset for link predictioncited by 0
- 2025Frequent subgraph-based persistent homology for graph classificationcited by 0
- 2025Frequent subgraph-based persistent homology for graph classification31 Dec 2025
- 2024In-Context Learning of Physical Properties: Few-Shot Adaptation to Out-of-Distribution Molecular Graphs3 Jun 2024
- 2023Pattern Mining for Anomaly Detection in Graphs: Application to Fraud in Public Procurement19 Jun 2023
- 2023Farspredict: A benchmark dataset for link prediction26 Mar 2023
- 2022MDL-based Compressing Sequential Rules20 Dec 2022