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GraMI: Frequent Subgraph and Pattern Mining in a Single Large Graph

Summary: GraMI mines frequent subgraphs directly in one large graph, avoiding exhaustive instance enumeration by finding only the minimal instances needed to meet the support threshold. Extensions support transitive patterns, structural/semantic constraints, and false-positive-free approximation, yielding up to 100× speedups. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
h79c9d11640e859ad
Venue
VLDB
Year
2014
Pagerank
0.00012422544
Overall Rank
1,027 | 93.10%
DOI
10.14778/2732286.2732289

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{elseidy_vldb14,
        title = {{GraMI: Frequent Subgraph and Pattern Mining in a Single Large Graph}},
        author = {Elseidy, Mohammed and Abdelhamid, Ehab and Skiadopoulos, Spiros and Kalnis, Panos},
        journal = {PVLDB},
        series = {{VLDB} '14},
        volume = {7},
        number = {7},
        pages = {517--528},
        doi = {10.14778/2732286.2732289},
        url = {https://doi.org/10.14778/2732286.2732289},
        year = {2014}
}

Incoming Citations (Sorted by Pagerank)

Showing 23 of 23 citing papers.

Rank Citing Paper Year Venue Pagerank
2,469 Pangolin: An Efficient and Flexible Graph Mining System on CPU and GPU 2020 VLDB 8.4165523e-05
2,518 Fractal: A General-Purpose Graph Pattern Mining System 2019 SIGMOD 8.3533785e-05
3,498 COMMIT: A Scalable Approach to Mining Communication Motifs from Dynamic Networks 2015 SIGMOD 7.2551144e-05
4,068 Beyond Macrobenchmarks: Microbenchmark-based Graph Database Evaluation 2019 VLDB 6.8215122e-05
4,858 Association Rules with Graph Patterns 2015 VLDB 6.3793644e-05
5,901 Combining Sampling and Synopses with Worst-Case Optimal Runtime and Quality Guarantees for Graph Pattern Cardinality Estimation 2021 SIGMOD 5.9539374e-05
6,440 Maverick: Discovering Exceptional Facts from Knowledge Graphs 2018 SIGMOD 5.7842039e-05
7,243 Discovering Graph Functional Dependencies 2018 SIGMOD 5.5768239e-05
7,251 T-FSM: A Task-Based System for Massively Parallel Frequent Subgraph Pattern Mining from a Big Graph 2023 SIGMOD 5.574104e-05
7,708 Systems for Scalable Graph Analytics and Machine Learning: Trends and Methods 2025 VLDB 5.4718627e-05
7,939 GraphINC: Graph Pattern Mining at Network Speed 2023 SIGMOD 5.4223464e-05
8,037 Flexible and Feasible Support Measures for Mining Frequent Patterns in Large Labeled Graphs 2017 SIGMOD 5.4019783e-05
8,218 Towards Event Prediction in Temporal Graphs 2022 VLDB 5.3762638e-05
8,342 Mining Top-k Pairs of Correlated Subgraphs in a Large Network 2020 VLDB 5.3516819e-05
8,891 Efficient Top-k Frequent Subgraph Mining Using Tight Upper and Lower Bounds 2025 VLDB 5.2559789e-05
9,278 Ontological Pathfinding: Mining First-Order Knowledge from Large Knowledge Bases 2016 SIGMOD 5.203976e-05
9,296 TED: Towards Discovering Top-k Edge-Diversified Patterns in a Graph Database 2023 SIGMOD 5.1991444e-05
9,806 Making It Tractable to Catch Duplicates and Conflicts in Graphs 2023 SIGMOD 5.1257999e-05
9,860 GARUDA: A System for Large-Scale Mining of Statistically Significant Connected Subgraphs 2016 VLDB 5.1178924e-05
10,202 Sage: Parallel Semi-Asymmetric Graph Algorithms for NVRAMs 2020 VLDB 5.0610409e-05
10,786 MDS-FSM: Coverage-Based Frequent Subgraph Mining in Single Graphs 2026 VLDB 4.9793485e-05
10,788 Subgraph Enumeration: Beyond Tree Decomposition 2026 VLDB 4.9793485e-05
12,059 Approximate Pattern Matching in Massive Graphs with Precision and Recall Guarantees 2020 SIGMOD 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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