Abstract: Proximity search is the most frequent activity people do in order to get information about nearby things. During this search most of the users make use of mobile devices for performing this kind of search. The small screen and default keypad of these mobile devices limit the interactions between user and search server. In such case, the search must not be irrelevant to the user search, we need an efficient way to give query and get response. In this paper, we propose a personalization approach by means of which we will be able to capture userís interests and preferences by maintaining history of their choices. The search keywords are arranged into ontology. The search engine works on client-server model. Heavy tasks such as creation of ontology, maintaining history, performing search are done by the server, client acts as an interface between user and server. We prototype mobile search engine on Google Android Platform. The approach is given an application interface: shopping and navigation. Two approaches are implemented to accomplish the search: Ontology search and Semantic Ontology Search. From the comparison of retrieval times of a normal search engine and an ontological search engine, it has been found that, the retrieval effectiveness of the proposed system is higher than that of a search engine.

Keywords: Ontology search, personalization, mobile search engine, location preference.