An efficient query processing through clickthroughs in personalized mobile search engines

Since the contents stored in the web increases rapidly, we need to have an efficient search engine that retrieves the information as per the users interest and preference. So we propose a mobile search engine that personalizes users search with the help of the query that the user types and their click through activities. In mobile search engines location plays an important role, so we classify the searches by the user into content (i.e., non-geo) and location (i.e., geo) concepts and organize them into ontologies to create an ontology based, multi-facet (OMF) profile that captures users content and location interest which in turn improves the search accuracy. Here users location is traced using Global Positioning System. Using a client server architecture the click through data are stored ant the client side and concept extraction training and reranking is done at the server side.