PWS Using Learned User Profiles by Greedy DP and IL

Abstract

From this method no assurance to the user privacy and also no securities were providing to their data. Hence users were afraid for their private information during search has become a major barrier. They were many techniques were proposed by researchers most of that based on the server side, it has provide less security. For minimizing the privacy risk here propose the client side based technique with the combination of Greedy method to prevent the user data that we applied in Knowledge mining area. Proposed framework called UPS that can adaptively generalize profiles by queries while respecting user’s privacy requirements. Proposed work consists two greedy algorithms, namely GreedyDP and GreedyIL, for runtime generalization.
Index Terms— Privacy Protection; profile; personalized web search; risk; UPS