• Suvarna Veer
• Rajani Sajjan

Personalized web search (PWS) improves the level of various search services on the Internet. But because of lack of user’s private search information during search it is difficult for the wide proliferation of PWS. We study privacy protection in PWS applications which helps to structure user preferences as hierarchical user profiles. We propose a PWS framework that helps to generalize profiles by queries while respecting user specified privacy requirements. We are aiming at striking a balance between two main factors that evaluate the utility of personalization and the privacy risk of exposing the generalized profile. We present two algorithms first is SSM and cosine similarity algorithm for runtime generalization and second is ranking based on mean value of similar links.

Data security, public server, SSM, PWS, cosine similarity

"Providing Privacy in Domain Specific Search with SSM and Cosine Similarity", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.229-235, December-2018, Available :http://www.jetir.org/papers/JETIR1812129.pdf

"Providing Privacy in Domain Specific Search with SSM and Cosine Similarity", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp229-235, December-2018, Available at : http://www.jetir.org/papers/JETIR1812129.pdf