A protection PWS system UPS to sum up profiles as per client security prerequisites
Journal Title: International Journal of Science Engineering and Advance Technology - Year 2015, Vol 3, Issue 10
Abstract
Personalized web search 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. We study privacy protection in PWS applications that model user preferences as hierarchical user profiles. We propose a PWS framework called UPS that can adaptively generalize profiles by queries while respecting user-specified privacy requirements. Our 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. We present two greedy algorithms, namely GreedyDP and GreedyIL, for runtime generalization. We also provide an online prediction mechanism for deciding whether personalizing a query is beneficial. Extensive experiments demonstrate the effectiveness of our framework. The experimental results also reveal that GreedyIL significantly outperforms GreedyDP in terms of efficiency.
Authors and Affiliations
Tadapaneni Sambasivarao| Dept. of CSE, Vignan's Lara Institute of Technology and Science, Guntur, Andhra Pradesh, Lukka Srikanth| Dept. of CSE, Vignan's Lara Institute of Technology and Science, Guntur, Andhra Pradesh
Keywords
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