Analyzing Privacy Protection in Personalized Web Search

Abstract

Personalized Web Search (PWS) is very effective in improving the quality of search services on the internet. The information on internet has increased day by day and user demand for the accurate result, for the accurate result the user has option to PWS. PWS works on the basis of information that user provide to search provider, the current result based on that information. This paper model makes use of hierarchical user profiles, it simultaneously maintaining privacy protection required by the user. Greedy DP (Discriminating Power) & Greedy IL (Information Loss) are used for runtime generalization and it have online prediction that query requires personalization or not.