

Study on Protecting Privacy in Personalized Web Search
Abstract
The size of the Internet increasing as per to grow the users of search providers continually demand search results that are accurate to their demands. Personalized Search is one of the options available to users in order to sculpt search results based on their personal data returned to them provided to the search provider. This brings up fears of privacy issues however, as users are typically anxious to revealing personal info to an often faceless service provider along the Internet. This work proposes to administer with the privacy issues surrounding personalized search and discusses ways that privacy can be improved so that users can get easier with the dismissal of their personal information in order to obtain more precise search results.
Keywords
References
Lidan Shou, H. Bai, Ke Chen, and G. Chen, ‘’Supporting Privacy Protection in Personalized Web Search’’, IEEE Transactions on Knowledge and Data Engineering, volume. 26, no. 2, Feb 2014.
L. Shou, G. Chen, Y. Gao, K. Chen, and H. Bai ‘’Ups: Efficient Privacy Protection in Personalized Web Search’’, Proc. 34th Int’l ACM SIGIR Conf. Research and Development in Information, pp. 615-624, 2011.
A. Viejo and J. Castell_a-Roca, “Using Social Networks to Distort Users’ Profiles Generated by Web Search Engines”, Computer Networks, volume. 54, no. 9, pp. 1343-1357, 2010.
Y. Zhu, C. Verdery and L. Xiong, “Anonymizing User Profiles for Personalized Web Search”, Proc. 19th Int’l Conf. World Wide Web (WWW), pp. 1225-1226, 2010.
A. Krause and E. Horvitz, “A Utility-Theoretic Approach to Privacy in Online Services”, J. Artificial Intelligence Research, vol. 39, pp. 633-662, 2010.
Shen, Xuehua, Bin Tan, and Cheng Xiang Zhai. "Implicit user modeling for personalized search." Proceedings of the 14th ACM international conference on Information and knowledge management. ACM, 2005.
T. Joachims, L. Granka, B. Pang, H. Hembrooke, and G. Gay, “Accurately Interpreting Clickthrough Data as Implicit Feedback,” Proc. 28th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR ’05), pp. 154-161, 2005.
Shen, Xuehua, Bin Tan, and Cheng Xiang Zhai. "Context-sensitive information retrieval using implicit feedback." Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval. ACM, 2005.
Xu, Yabo, et al. "Online anonymity for personalized web services." Proceedings of the 18th ACM conference on Information and knowledge management. ACM, 2009.
A. Viejo and J. Castell_a-Roca, “Using Social Networks to Distort Users’ Profiles Generated by Web Search Engines,” Computer Networks, vol. 54, no. 9, pp. 1343-1357, 2010.
Xu, Yabo, et al. "Privacy-enhancing personalized web search." Proceedings of the 16th international conference on World Wide Web. ACM, 2007
Xiao, Xiaokui, and Yufei Tao. "Personalized privacy preservation", Proceedings of the 2006 ACM SIGMOD international conference on Management of data. ACM, -2006.
B.Upender, Bathula Revathi, “Analysis on Supporting Privacy Protection in Personalized Web Search”, International Journal of Research and Computational Technology, Vol.7 Issue.2.
Khwaja Aamer, Dr. A. S. Hiwale, “A Survey on Privacy Protection in Personalized Web Search”, International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064.
J. Teevan, S.T. Dumais, and E. Horvitz, “Personalizing Search via Automated Analysis of Interests and Activities,” Proc. 28th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), pp. 449-456, 2005.
M. Spertta and S. Gach, “Personalizing Search Based on User Search Histories,” Proc. IEEE/WIC/ACM Int’l Conf. Web Intelligence (WI), 2005.
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.
J. Teevan, S.T. Dumais, and D.J. Liebling, “To Personalize or Not to Personalize: Modeling Queries with Variation in User Intent,” Proc. 31st Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), pp. 163-170, 2008.
Refbacks
- There are currently no refbacks.

This work is licensed under a Creative Commons Attribution 3.0 License.