State-of-the-art review on relevance of genetic algorithm to internet web search

Authors:
Kehinde Agbele;Ademola Adesina;Daniel Ekong;Oluwafemi Ayangbekun
Affiliations:
Department of Computer Science, University of the Western Cape, Cape Town, South Africa;Department of Computer Science, University of the Western Cape, Cape Town, South Africa;Department of Mathematical Sciences, Ekiti State University, Ado-Ekiti, Ekiti State, Nigeria;College of Information and Communication Technology, Crescent University, Abeokuta, Ogun-State, Nigeria
Venue:
Applied Computational Intelligence and Soft Computing
Year:
2012

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Abstract

People use search engines to find information they desire with the aim that their information needs will be met. Information retrieval (IR) is a field that is concerned primarily with the searching and retrieving of information in the documents and also searching the search engine, online databases, and Internet. Genetic algorithms (GAs) are robust, efficient, and optimizated methods in a wide area of search problems motivated by Darwin's principles of natural selection and survival of the fittest. This paper describes information retrieval systems (IRS) components. This paper looks at how GAs can be applied in the field of IR and specifically the relevance of genetic algorithms to internet web search. Finally, from the proposals surveyed it turns out that GA is applied to diverse problem fields of internet web search.