| DC Field | Value | Language |
|---|
| dc.contributor.author | Dzenhaliou, D. I. | - |
| dc.contributor.author | Sarvanov, V. I. | - |
| dc.coverage.spatial | Минск | en_US |
| dc.date.accessioned | 2024-02-27T09:37:18Z | - |
| dc.date.available | 2024-02-27T09:37:18Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.citation | Dzenhaliou, D. I. Improving efficiency of VF3 and VF3-light algorithms for sparse graphs / D. I. Dzenhaliou, V. I. Sarvanov // Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) : Proceedings of the 16th International Conference, October 17–19, 2023, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2023. – P. 300–304. | en_US |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/54403 | - |
| dc.description.abstract | Researchers have made notable progress in improv-
ing the way we fi nd isomorphic subgraphs in labeled or unlabeled
graphs by focusing on effi ciency. One group of algorithms,
known as the VF series, has consistently shown its effectiveness,
especially when dealing with large sparse graphs. In this paper,
we introduce a new method that leverages machine learning
capabilities, aiming to improve the performance of VF3 and VF3-
light algorithms in solving the specifi ed problem. Also, we propose
a new parallelization scheme for VF3 and VF3-light algorithms. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | BSU | en_US |
| dc.subject | материалы конференций | en_US |
| dc.subject | graph | en_US |
| dc.subject | algorithm | en_US |
| dc.subject | isomorphism | en_US |
| dc.title | Improving efficiency of VF3 and VF3-light algorithms for sparse graphs | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023)
|
