Problem statement: The huge number of information on the web as well as the growth of new inexperienced users creates new challenges for information retrieval. It has become increasingly difficult for these users to find relevant document s that satisfy their individual needs. Certainly th e current search engines (such as Google, Bing and Yahoo) offer an efficient way to browse the web content. However, the result quality is highly based on uses queries which need to be more precise to find rele vant documents. This task still complicated for the majo rity of inept users who cannot express their needs with significant words in the query. For that reason, we believe that a reformulation of the initial user's query can be a good alternative to improve the informatio n selectivity. This study proposed a novel approach and presents a prototype system called Profile-base d Reformulation System (PRESY) for information retrieval on the web. Approach: It used an incremental approach to categorize user s by constructing a contextual base. The latter was composed of two typ es of context (static and dynamic) obtained using t he users' profiles. The architecture proposed was imp lemented using .Net environment to perform queries reformulating tests. Results: The experiments gave at the end of this article sh ow that the precision of the returned content is effectively improved. The tests were performed with the most popular searching engine (i.e., Google, Bind and Yahoo) selected in particul ar for their high selectivity. Among the given resu lts, we found that query reformulation improve the first th ree results by 10.7 and 11.7% of the next seven ret urned elements. So as we could see the reformulation of u sers' initial queries improves the pertinence of re turned content. Conclusion/Recommendations: Therefore, we believed that the exploitation of co ntextual data based on users' profiles could be a very good way t o reformulate user query. This complementary mechanism would be highly improve the quality of information retrieval on the web. In the other side, we believe that more the user's profiles are properly constructed more the returned documents are relevant. Thus, the approach of constructing profiles needs t o be deeply studied in order to have more represent ative elements. Additional data like historical searching and browsing activity of a user can be also combin ed to improve the query reformulation. This constitutes a part of our perspectives to improve PRESY.
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