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Articles by Bayo Adetunmbi
Total Records ( 1 ) for Bayo Adetunmbi
  Kehinde Agbele , Bayo Adetunmbi , Segun Olajide and Daniel Ekong
  Today, searching information in the web or in any kind of document collection has become one of the most regular activities. Though, user queries can be formulated in a way that hinders the recovery of the requested information. The objective of automatic query reformulation is to improve the predicted relevance of the retrieved documents. This study describes a new OPTRANDOC algorithm; an acronym for OPTmize RANking DOCuments procedure used to modify the set of keyword terms from the information sources that compose a user query with the use of a SMS based on HIV/AIDS content-related corpus. The proposed method extracts the frequency of SMS-query keyword terms that appears within the context of (FAQs) databases. This study presents a novel framework of Information Retrieval Systems (IRS). The developed OPTRANDOC procedure is used as an evaluation measure. Researchers apply TFIDF method to obtain the trial results for which the SMS corpus provides its different forms that is promising with its attractive results.
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