Privacy Protection in Personalized Web Search
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 3
Abstract
Since the content in Internet is growing rapidly, the search provider users demand accurate search result as per their need. One of the options available to users is personalized web search which presents search result based on the personal data of user provided to the search provider. However, users’ unwillingness to share their private information during search has become the major barrier for personalized web search. This paper models preference of users as hierarchical user profiles. It proposes a framework called UPS which generalizes profile at the same time maintaining privacy requirement specified by user. Two greedy algorithms namely GreedyDP and GreedyIL are used for runtime generalization. Also, an online prediction mechanism to decide whether to personalize a query or not is provided in this paper.
Authors and Affiliations
Anuja Agnihotri, Jyoti Kale, Priyanka Patil, Prof. Sheetal Thakare
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