文章基本信息

标题：Relevance of Genetic Algorithm Strategies in Query Optimization in Information Retrieval
本地全文：下载
作者：Anubha Jain ; Swati V. Chande ; Preeti Tiwari 等
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2014
卷号：5
期号：4
页码：5921-5927
出版社：TechScience Publications
摘要：The augmentation of digital information on the Web has proliferated informational needs and expectations of the seekers, resulting in insistent need of more advanced search tools, that are able to respond to the informational requirements within an organization. The user may formulate a search query in a way that can obscure the useful documents to be retrieved. The objective of query optimization is to transform the query into an effective form to improve the quality of recovered information and to reduce the computational burden in processing document text at query time. Genetic algorithms are efficient and robust methods, employed widely in optimization of a variety of search problems, motivated by Darwin’s principles of natural selection and survival of the fittest. This paper reviews relevance of genetic algorithms to improve upon the user queries in the field of Information Retrieval
关键词：Query Optimization; Information Retrieval;Genetic Algorithm; Genetic Operators; Ranking.