International audienceThis work falls in the areas of information retrieval and semantic web, and aims to improve the evaluation of web search tools. Indeed, the huge number of information on the web as well as the growth of new inexperienced users creates new challenges for information retrieval; certainly the current search engines (such as Google, Bing and Yahoo) offer an efficient way to browse the web content. However, this type of tool does not take into account the semantic driven by the query terms and document words. This paper proposes a new semantic based approach for the evaluation of information retrieval systems; the goal is to increase the selectivity of search tools and to improve how these tools are evaluated. The test of the proposed approach for the evaluation of search engines has proved its applicability to real search tools. The results showed that semantic evaluation is a promising way to improve the performance and behavior of search engines as well as the relevance of the results that they return

The crucial role of the evaluation in the development of the information retrieval tools is useful evidence to

No abstract

In this paper, we propose a new approach for locating and retrieving documents; the search process is guided by the 'AnimOnto' domain ontology that we have constructed for this purpose. This ontology is used at two different stages: First, for the semantic indexing of documents, in this stage the representative concepts of each document are selected by a projection of the ontology on the document by attaching their terms to the 'AnimOnto' concepts. Then, during the semantics queries reformulation; in this stage we exploit the semantic links between concepts to expand the initial query. To validate these proposals, we have implemented the 'AnimSe Finder' tool (Animal Semantic Finder) which materializes the different phases of the proposed approach. The obtained scores show that the semantic indexing and the queries reformulation have generated a gain of 13.06 in terms of recall and 16.13 in terms of precision, which significantly reduces the documentary noise and silence. General TermsSemantic Web, Information Retrieval.

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 documents that satisfy their individual needs. Certainly the 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 relevant documents. This task still complicated for the majority 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 information selectivity. This study proposed a novel approach and presents a prototype system called Profile-based Reformulation System (PRESY) for information retrieval on the web. Approach: It used an incremental approach to categorize users by constructing a contextual base. The latter was composed of two types of context (static and dynamic) obtained using the users' profiles. The architecture proposed was implemented using .Net environment to perform queries reformulating tests. Results: The experiments gave at the end of this article show 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 particular for their high selectivity. Among the given results, we found that query reformulation improve the first three results by 10.7 and 11.7% of the next seven returned elements. So as we could see the reformulation of users' initial queries improves the pertinence of returned content. Conclusion/Recommendations: Therefore, we believed that the exploitation of contextual data based on users' profiles could be a very good way to 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 to be deeply studied in order to have more representative elements. Additional data like historical searching and browsing activity of a user can be also combined to improve the query reformulation. This constitutes a part of our perspectives to improve PRESY