Internet search engines use Web crawlers to download data from the Web. The crawled data is stored on centralized servers, where it is parsed and indexed. The importance of a Web page is an inherently subjective matter, which depends on the reader's interests, knowledge and attitudes. Search engines use a ranking algorithm to determine the order in which matching web pages are returned on the results page [12]. They build indices mostly based on keyword occurrence, link popularity and frequency for query negotiation using these indices. Using these connectivity based algorithms, they measure the quality of each individual page so that users will receive a ranked page list for their queries. These search engines perform search with respect to the query fired by the user without considering the perspective of the user. Thus giving results based on a generalized perspective. This paper presents a system architecture that would work as a subordinate to a normal search engine by taking its results, calculating the relevance of these results with respect to the user's perspective (profile) and then displaying the results along with its relevance to the user.