Efficiency of genetic algorithm for subject search queries
- 32 Downloads
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.
Keywords and phrasesConvergence genetic algorithm fitness function population ranking relevance search precision search query
Unable to display preview. Download preview PDF.
- 1.H. Chu, Information representation and retrieval in the digital age (American Society for Information Science and Technology by Information Today Inc.,Medford, NJ, 2010).Google Scholar
- 9.M. H. Marghny and A. F. Ali, AIML’05 Conference, CICC, Cairo, Egypt, 82–87 (2005).Google Scholar
- 12.R. L. Cecchini et al., Journal of the American Society for Information Science and Technology. 61 (6), 1258–1274 (2010).Google Scholar
- 15.V. K. Ivanov, B. V. Palyukh, and A. N. Sotnikov, Programmnyye produkty i sistemy. 4, 197–202 (2013).Google Scholar
- 17.V. K. Ivanov, Innovatsii v nauke. (25), 8–15 (2013).Google Scholar
- 19.V. K. Ivanov and P. I. Meskin, Programmnye produkty i sistemy. 4, 118–126 (2014).Google Scholar
- 20.J. H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence (The MIT Press, 1992).Google Scholar
- 21.V. K. Ivanov and B. V. Palyukh, OSTIS-2015 Materialy konferencii, 471–476 (2015).Google Scholar
- 23.K. Collins-Thompson et al., The Twenty-Second Text REtrieval Conference (TREC 2013) Proceedings, SP 500–302 (2014).Google Scholar
- 24.J. R. Frank et al., The Twenty-Second Text Retrieval Conference (TREC 2013) Proceedings, SP 500–302 (2014).Google Scholar