Efficiency of genetic algorithm for subject search queries
- Authors: Ivanov V.K.1, Palyukh B.V.1, Sotnikov A.N.1
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Affiliations:
- Tver State Technical University Joint Supercomputer Centre of the Russian Academy of Sciences
- Issue: Vol 37, No 3 (2016)
- Pages: 244-254
- Section: Article
- URL: https://journals.rcsi.science/1995-0802/article/view/197627
- DOI: https://doi.org/10.1134/S1995080216030124
- ID: 197627
Cite item
Abstract
The article presents and generalizes the results on some performance indicators of genetic algorithm developed by authors and applied to effective search queries and selection of relevant results after document subject search. It is shown that the developed technology expands opportunities of semantic search and increases the number of the found relevant results. In particular, we made an effort to show the ability of the developed algorithm to achieve the neighborhood of the fitness function in a finite number of steps, to provide higher precision of search in comparison with the well-known search engines of the Internet as well as to provide the acceptable semantic relevance of the found documents.
About the authors
V. K. Ivanov
Tver State Technical University Joint Supercomputer Centre of the Russian Academy of Sciences
Author for correspondence.
Email: mtivk@tstu.tver.ru
Russian Federation, Tver
B. V. Palyukh
Tver State Technical University Joint Supercomputer Centre of the Russian Academy of Sciences
Author for correspondence.
Email: pboris@tstu.tver.ru
Russian Federation, Tver
A. N. Sotnikov
Tver State Technical University Joint Supercomputer Centre of the Russian Academy of Sciences
Author for correspondence.
Email: asotnikov@jscc.ru
Russian Federation, Tver