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http://dx.doi.org/10.5391/IJFIS.2003.3.2.222

Query Space Exploration Model Using Genetic Algorithm  

Lee, Jae-Hoon (Dept. of Computer Science, Graduate School, Chosun Univ.)
Lee, Sung-Joo (Dept. of Computer Engineering, Chosun Univ.)
Publication Information
International Journal of Fuzzy Logic and Intelligent Systems / v.3, no.2, 2003 , pp. 222-226 More about this Journal
Abstract
Information retrieval must be able to search the most suitable document that user need from document set. If foretell document adaptedness by similarity degree about QL(Query Language) of document, documents that search person does not require are searched. In this paper, showed that can search the most suitable document on user's request searching document of the whole space using genetic algorithm and used knowledge-base operator to solve various model's problem.
Keywords
Query; IR; Gene Algorithm;
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  • Reference
1 Boughanem M and Soule-Dupuy, Query modification based on relevance backpropagation. In: Proceedings of the 5th International Conference on Computer Assisted Information Searching on Internet, Montreal, pp. 469-487, 1997
2 Haines D and Croft WB Relevance feedback and inference networks, In: ACM SIGIR International Conference on Research and Development in Information Retrieval, pp.2-11, 1993
3 Robertson S and Walker S, On relevance weights with little relevance information. ACM/SIGIR International Conference on Research and development in Information Retrieval, pp. 16-24, 1997
4 Sebag M and Schoenauer M, Controle un algorithms genetique. Revued' intelligence artificielle, 2/3:389-428, 1996
5 Goldberg DE Algorithmes genetiques. Exploration, optimisation et apprentissage automatique. addison Wesley, France, 1994
6 Gordon M Probabilistic and genetic algorithms for document retrieval, Communications of the ACM, pp. 1208-1218, 1988
7 Yang JJ and Korhage R, Query optimization in information retrieval using genetic algorithms. ICGA, 1993
8 Chen Machine learning for information retrieval: Neural networks, symbolic learning and genetic algorithms. JASIS, 46(3): 194-216, 1995   DOI   ScienceOn
9 Harmaqn D TREC overview, In: 6th International Conference on Text Retrieval TREC6, November 21-23. Harman DK, ed. NIST SP, pp. 1-24, 1997
10 Davis Handbook of Genetic Algorithms. Van Nostram Reinhold, New York, 1991