Provision of Relevant Results on web search Based on Browsing History

Different users submit a query to a web search engine with different needs. The general type of search engines follows the "one size fits all" model which is not flexible to individual users resulting in too many answers for the query. In order to overcome this drawback, in this paper, we propose a framework for personalized web search which considers individual's interest introducing intelligence into the traditional web search and producing only relevant pages of user interest. This proposed method is simple and efficient which ensures quality suggestions as well as promises for effective and relevant information retrieval. The framework for personalized web search engine is based on user past browsing history. This context is then used to make the web search more personalized. The results are encouraging.