Abstract:
Searching for relevant information has become a skillful art in the current scenario of vast amount of available data. Often we may end up with a large amount of unrelated data. Many a times it requires a lot of human effort to choose from the presented information, after putting a lot of effort to find the information the user has no way to help other users who are searching for similar information. At most now a day's search engines (like Google) are giving results based on self history. In this we are proposing an Agent based frame work to make the users, find the relevant information more quickly not only by using his/her history but also by using other users search experience. For this we are using a measure called Query distance to find the similarity between the two queries. Problem occurs when the users of different domains submits the same query with different intensions for this we are using the categories. To make the Query distance more appropriate we are using the semantics of the query also when finding the query distance
