Mobile search engine is a program that searches for and identifies items in adatabase that correspond to keywords or characters specified by the user, used especially for finding particular sites on the World Wide Web.A major problem in mobile search is that the interactions between the users and search engines are limited by the small form factors of the mobile devices. As a result, mobile users tend to submit shorter, hence, more ambiguous queries compared to their web search counterparts. In order to return highly relevant results to the users, mobile search engines must be able to profile the users interests and personalize the search results according to the users profiles. A personalized mobile search engine (PMSE) that


captures the users preferences in the form of concepts by mining their click through data. Due to the importance of location information in mobile search, PMSE classifies these concepts into content concepts and location concepts. The user preferences are organized in an ontology based, multifaceted user profile, which are used to adapt a personalized ranking function for rank adaptation of future search results. To characterize the diversity of the concepts associated with a query and their relevance’s to the users need, four entropies are introduced to balance the weights between the content and location facets. Based on the client-server model, a detailed architecture and design for implementation of PMSE is also presented. In implemented system, the client collects and stores locally the clickthrough data to protect privacy, whereas heavy tasks such as concept extraction, training, and reranking are performed at the PMSE server. User get the information depending upon query and nearby location.