SUSTAINING PRIVACY PROTECTION IN PERSONALIZED WEB SEARCH OVER RE-RANKING WITH CACHE SERVICES MODEL IN WEB DATABASE

P.Vinothini; M.Jothilakshmi

Article Information

Published In Volume 2, Issue 8 (2016)
Publication Date July 31, 2026
Manuscript ID IJCRCST-AUGUST16-12
Article Type Research Paper
Pages 946 - 950
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Abstract

Personalized web search (PWS) has demonstrated its effectiveness in improving the quality of various search services on the Internet. However, evidences show that users’ reluctance to disclose their private information during search has become a major barrier for the wide proliferation of PWS. This paper analysis a privacy protection in PWS applications that model user preferences as hierarchical user profiles. This paper proposes a PWS framework called UPS that can adaptively generalize profiles by queries while respecting user-specified privacy requirements. The proposed runtime generalization aims at striking a balance between two predictive metrics that evaluate the utility of personalization and the privacy risk of exposing the generalized profile. The paper presents a greedy algorithm, namely Enhanced GreedyIL, for runtime generalization. It also provides an online prediction mechanism for deciding whether personalizing a query is beneficial.

Keywords

Personalized web search profile Catch base Search Tree Fusion Re-ranking Algorithm Security privacy.

Authors

P.Vinothini

M.Jothilakshmi

How to Cite this Article

P.Vinothini, M.Jothilakshmi (2016). "SUSTAINING PRIVACY PROTECTION IN PERSONALIZED WEB SEARCH OVER RE-RANKING WITH CACHE SERVICES MODEL IN WEB DATABASE". International Journal of Contemporary Research in Computer Science and Technology, 2(8), pp. 946-950.