Author : Mrs. Priyanka Deulkar 1
Date of Publication :7th July 2015
Abstract: One user hundred needs on internet. As more and more queries are being searched on the web, it is increasingly difficult to let the search engine know in what context user wants to search. Coping with ambiguous queries has long been an important part in the research of Information Retrieval, but still remains to be a challenging task. Personalized search has recently got significant attention to address this challenge in the web search community, based on the premise that a users general preference may help the search engine disambiguate the true intention of a query. In this paper, we implement an algorithm that returns relevant results to users based on their preferences keeping sensitive data more secure. Our experiments show that user's sensitive preferences can be preserved accurately from attacks. Our scheme provides an affordable overhead while offering privacy benefits to the users.
- Susan Gauch, Mirco Speretta, Aravind Chandramouli, and Alessandro Micarelli, “User profiles for personalized information Access” Springer LNCS 4321.
- G. Chen, H. Bai, L. Shou, K. Chen, and Y. Gao, “Ups: Efficient Privacy Protection in Personalized Web Search,” Proc. 34th Int’l ACM SIGIR Conf. Research and Development in Information, pp. 615-624, 2011.
- Hoashi, K., Matsumoto, K., Inoue, N., Hashimoto, K.: Document Filtering method using non-relevant information profile. In: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Athens, Greece, July 24-28 (2000) 176-183.
- Kim, H., Chan, P. “Learning implicit user interest hierarchy for context in personalization. In: Proceedings of IUI’ 03, Miami, Florida, January 12-15 (2003) 101- 108.
- M. Spertta and S. Gach, “Personalizing Search Based on User Search Histories,” Proc. IEEE/WIC/ACM Int’l Conf. Web Intelligence(WI), 2005.
- B. Tan, X. Shen, and C. Zhai, “Mining Long-Term Search History to Improve Search Accuracy,” Proc. ACM SIGKDD Int’l Conf. Knowledge Discovery and Data Mining (KDD), 2006.
- F. Qiu and J. Cho, “Automatic Identification of User Interest for Personalized Search,” Proc. 15th Int’l Conf. World Wide Web(WWW), pp. 727-736, 2006.
- J. Pitkow, H. Schutze, T. Cass, R. Cooley, D. Turnbull, A. Edmonds, E. Adar, and T. Breuel, “Personalized Search,” Comm.ACM, vol. 45, no. 9, pp. 50-55, 2002.
- Z. Dou, R. Song, and J.-R.Wen, “A Large-Scale Evaluation and Analysis of Personalized Search Strategies,” Proc. Int’l Conf. World Wide Web (WWW), pp. 581-590, 2007
- X. Shen, B. Tan, and C. Zhai, “Privacy Protection in Personalized Search,” SIGIR Forum, vol. 41, no. 1, pp. 4-17, 2007
- Y. Xu, K. Wang, B. Zhang, and Z. Chen, “PrivacyEnhancing Personalized Web Search,” Proc. 16th Int’l Conf. World Wide Web(WWW), pp. 591-600, 2007
- Liu, F., Yu, C., Meng, W.: Personalized web search by mapping user queries to categories. In: Proceedings CIKM’02, Mclean, Virginia, November 4-9 (2002) 558- 565.
- K. Sugiyama, K. Hatano, and M. Yoshikawa, “Adaptive Web Search Based on User Profile Constructed without any Effort from Users,” Proc. 13th Int’l Conf. World Wide Web (WWW), 2004.
- "A Study On Securing Privacy In Personalized Web Search" in International Journal Of Engineering And Computer Science Volume 4 Issue 3 March 2015 .