A Survey on Subgraph Counting: Concepts, Algorithms and Applications to Network Motifs and Graphlets
Not on the map. Why?
Abstract (arXiv)
Computing subgraph frequencies is a fundamental task that lies at the core of several network analysis methodologies, such as network motifs and graphlet-based metrics, which have been widely used to categorize and compare networks from multiple domains. Counting subgraphs is however computationally very expensive and there has been a large body of work on efficient algorithms and strategies to make subgraph counting feasible for larger subgraphs and networks. This survey aims precisely to provide a comprehensive overview of the existing methods for subgraph counting. Our main contribution is a general and structured review of existing algorithms, classifying them on a set of key characteristics, highlighting their main similarities and differences. We identify and describe the main conceptual approaches, giving insight on their advantages and limitations, and provide pointers to existing implementations. We initially focus on exact sequential algorithms, but we also do a thorough survey on approximate methodologies (with a trade-off between accuracy and execution time) and parallel strategies (that need to deal with an unbalanced search space).
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 29 Oct 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 2; 2023: 3.
5 papers.
- 2022Random graph matching at Otter's threshold via counting chandelierscited by 25
- 2023Breaking the Entanglement of Homophily and Heterophily in Semi-supervised Node Classificationcited by 19
- 2023Taming graph kernels with random featurescited by 17
- 2023DeSCo: Towards Generalizable and Scalable Deep Subgraph Countingcited by 4
- 2022Reinforcement Learning Enhanced Weighted Sampling for Accurate Subgraph Counting on Fully Dynamic Graph Streamscited by 3
- 2023Breaking the Entanglement of Homophily and Heterophily in Semi-supervised Node Classification7 Dec 2023
- 2023DeSCo: Towards Generalizable and Scalable Deep Subgraph Counting16 Aug 2023
- 2023Taming graph kernels with random features29 Apr 2023
- 2022Reinforcement Learning Enhanced Weighted Sampling for Accurate Subgraph Counting on Fully Dynamic Graph Streams13 Nov 2022
- 2022Random graph matching at Otter's threshold via counting chandeliers25 Sep 2022