The framework of social web search mines past activities of the user in his/her social network to identify the user preferences for items of different topics/categories posted by users contacts.A Naive Bayes approach is used in category determination process and the corresponding probabilities are mined. All items in the list returned by the search process are evaluated and the top items are recommend to the user.Experiments demonstrate that both the precision and recall values of search results are dramatically enhanced compared to only filtering by contacts.One immediate extension to framework can be to discover expertise

and also improve the expertise locator mechanism.