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

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dc.contributor.authorAgbele, Kehinde K.
dc.contributor.authorAdesina, Ademola Olusola
dc.contributor.authorEkong, Daniel
dc.contributor.authorAyangekun, Oluwafemi
dc.date.accessioned2014-02-20T14:21:13Z
dc.date.available2014-02-20T14:21:13Z
dc.date.issued2012
dc.description.abstractPeople 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.en_US
dc.identifier.citationAgbele, K.K., et al. (2012). State-of-the-art review on relevance of genetic algorithm to internet web search. Applied Computational Intelligence and Soft Computing, volume 2012: Article ID 152385en_US
dc.identifier.issn1687-9724
dc.identifier.urihttp://hdl.handle.net/10566/1030
dc.language.isoenen_US
dc.privacy.showsubmitterFALSE
dc.publisherHindawi Publishing Corporationen_US
dc.rightsCopyright © 2012 Agbele et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.source.urihttp://dx.doi.org/10.1155/2012/152385
dc.status.ispeerreviewedTRUE
dc.subjectInformation retrievalen_US
dc.subjectGenetic algorithmsen_US
dc.titleState-of-the-art review on relevance of genetic algorithm to internet web searchen_US
dc.typeArticleen_US

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