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Asian Journal of Information Technology
Year: 2012  |  Volume: 11  |  Issue: 3  |  Page No.: 117 - 124

State of the Art Review on Relevance of Genetic Algorithm to Internet Web Search

Kehinde Agbele, Ademola Adesina, Daniel Ekong and Oluwafemi Ayangbekun    

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 optimization methods in a wide area of search problems motivated by Dawn’s principles of natural selection and survival-of-the-fittest. This study presents a novel framework of Information Retrieval Systems (IRS). This study 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 to internet web search.

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