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https://elib.bsu.by/handle/123456789/306256| Title: | Improving efficiency of VF3 and VF3-light algorithms for sparse graphs |
| Authors: | Dzenhaliou, Daniil I. Sarvanov, Vladimir I. |
| Keywords: | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика |
| Issue Date: | 2023 |
| Publisher: | Minsk : BSU |
| Citation: | Pattern Recognition and Information Processing (PRIP’2023). Artificial Universe: New Horisont : Proceedings of the 16 th International Conference, Belarus, Minsk, October 17–19, 2023 / Belarusian State University : eds. A. Nedzved, A. Belotserkovsky. – Minsk : BSU, 2023. – Pp. 300-304. |
| Abstract: | Researchers have made notable progress in improving the way we find isomorphic subgraphs in labeled or unlabeled graphs by focusing on efficiency. 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 specified problem. Also, we propose a new parallelization scheme for VF3 and VF3-light algorithms |
| URI: | https://elib.bsu.by/handle/123456789/306256 |
| ISBN: | 978-985-881-522-6 |
| Licence: | info:eu-repo/semantics/openAccess |
| Appears in Collections: | 2023. Pattern Recognition and Information Processing (PRIP’2023). Artificial Intelliverse: Expanding Horizons |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 300-304.pdf | 196,73 kB | Adobe PDF | View/Open |
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