  This 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.
