Abstract:

Generic search engines are important for retrieving relevant information from Web. However these engines are not very effective since they follow the "one size fits all" model which is not adaptable because of the diversity of the user interests and the ambiguity of the user query. Indeed, current search engines are based on simple query-document matches without considering the user preferences and interests. Personalized search aims at solving this problem by modeling search interests of the user in a profile and exploiting it to improve the search process. One of the challenges in search personalization is how to properly model user’s search interests. Another challenge is how to effectively exploit these models to enhance the search quality. In this paper, we propose a personalization approach for construction and exploiting a multidimensional semantic user model in the context of COTS based development. This user model is used for improving the performance of a COTS component specialized search engine. Experimental results show that using our user model improves COTS components search quality by providing users with the most relevant results at the top of the search results list.