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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.
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.
