The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
A survey of frequent subgraph mining algorithms
Abstract
Graph mining is an important research area within the domain of data mining. The field of study concentrates on the identification of frequent subgraphs within graph data sets. The research goals are directed at: (i) effective mechanisms for generating candidate subgraphs (without generating duplicates) and (ii) how best to process the generated candidate subgraphs so as to identify the desired frequent subgraphs in a way that is computationally efficient and procedurally effective. This paper presents a survey of current research in the field of frequent subgraph mining and proposes solutions to address the main research issues.
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Mining frequent patterns without candidate generation
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Luna, J. M., Fournier‐Viger, P., & Ventura, S. (2019) · WIREs Data Mining and Knowledge Discovery · doi:10.1002/widm.1329 · Cited by 258
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Las-Casas, P., Papakerashvili, G., Anand, V., & Mace, J. (2019) · Proceedings of the ACM Symposium on Cloud Computing · doi:10.1145/3357223.3362736 · Cited by 42
Lin, W., Ma, M., Pan, D., & Wang, P. (2018) · 2018 IEEE 37th International Performance Computing and Communications Conference (IPCCC) · doi:10.1109/pccc.2018.8711092 · Cited by 29
ILP-assisted de novo drug design
Kaalia, R., Srinivasan, A., Kumar, A., & Ghosh, I. (2016) · Machine Learning · doi:10.1007/s10994-016-5556-x · Cited by 13
Metadata
- Authors
- Jiang, C., Coenen, F., & Zito, M.
- Venue
- The Knowledge Engineering Review
- Publisher
- Maximum Academic Press
- Published
- 2012-11-20
- Volume
- 28
- Issue
- 1
- Pages
- 75-105
- ISSN
- 0269-8889 (ISSN-L)
- 1469-8005
- OpenAlex
- W1985644065
- Cited by
- 346
- References
- 4
- FWCI
- 26.23
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jiang, C., Coenen, F., & Zito, M. (2013). A survey of frequent subgraph mining algorithms. The Knowledge Engineering Review. https://doi.org/10.1017/s0269888912000331
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