Information Retrieval using Semantic Web Browser - Personalized and Categorical Web Search

The semantic Web browsing offers several benefits for the users. The researchers have done lots of work in this area. The proposals specified by them are not used much effectively for accessing the information. The search engines built today serve all users, independent of the special needs of any individual user. Personalization of Web search for each user incorporating his/her interests would give effective information retrieval. A user may associate one or more categories to their query manually. We have improved the existing, Rocchio based algorithm to construct the general profile and user profile for personalization. In our proposed method, we have constructed a Web browser; the information is retrieved through the browser with the aid of category hierarchy. The category hierarchy information will be frequently updated and ranked as per the user's interest during his/her Web search dynamically, the information retrieved is also cached on the client side using semantic cache mechanism which improves the response time. We have experimentally proved that our technique personalizes the Web search and reduces the hits made by the search engine providing appropriate results and improves the retrieval efficiency