Privacy Enhanced Personalization in Content, Semantic and Location Approach

Abstract

Personalized web search improves the quality of various internet search services. Personalized mobile search engine plays a vital role in retrieving relevant information from online server to improve privacy in web search. It provides search results to user by capturing user search interests. Interests are classified based on user profile dynamically and search is categorized according to content, semantic and location. User preferred facet is extracted using ontology meaning whose click through data are saved to personalize results and perform re-ranking based on mine words. Semantic search provides relevant search results by applying porter stemmer algorithm with eliminate stop-words. Privacy issue is addressed by restricting user details available at client site, not maintained in server. This assures good ranking and controls privacy information. By enabling delete history function, the user can view general search. The proposed work aimed to enhance the approach of personalized mobile search mining with all the facets of the user. The work uses a client-server architecture which is prototyped on Android Platform.