Evaluation of Full Text Search Retrieval System

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dc.contributor.authorAruleba, K. D.
dc.contributor.authorAremu, D. R.
dc.contributor.authorOriogun, P. K.
dc.contributor.authorAgbele, Kehinde K.
dc.contributor.authorAgho, A. O.
dc.date.accessioned2019-07-12T11:33:55Z
dc.date.available2019-07-12T11:33:55Z
dc.date.issued2015
dc.description.abstractWith a number of search engines on the web and each with different indexing and ranking methods and different coverage, finding the one that gives the best results for a query becomes a bit challenging. The main problem however, that existing Search engines have to deal with is how to avoid irrelevant information and to retrieve the relevant ones. This current work presents a new approach for retrieving relevant information on the Web, by adopting breadth-First search algorithm. The implementation result of the retrieval system was analysed using recall and precision model for three departments at Elizade University. By learning from users’ behaviour, the approach can return very high quality search results, with a strongly reduced computing load.en_US
dc.identifier.citationAruleba, K. D., Aremu, D. R., Oriogun, P. K., Agbele, K. K., & Agho, A. O. (2015). Evaluation of Full Text Search Retrieval System. Nigeria Computer Society, 26, 154-159.en_US
dc.identifier.urihttp://repository.elizadeuniversity.edu.ng/handle/20.500.12398/295
dc.publisherNigeria Computer Societyen_US
dc.subjectFull-Text Retrieval Systemen_US
dc.subjectEvaluation Approachesen_US
dc.subjectIRen_US
dc.subjectSearch Enginesen_US
dc.subjectElizade Universityen_US
dc.titleEvaluation of Full Text Search Retrieval Systemen_US
dc.typeArticleen_US
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