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Refinement in Personalize Web Search System with Privacy Protection

by Anuradha K. Kudlikar, Meghana B. Nagori
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 6
Year of Publication: 2015
Authors: Anuradha K. Kudlikar, Meghana B. Nagori
10.5120/20555-2935

Anuradha K. Kudlikar, Meghana B. Nagori . Refinement in Personalize Web Search System with Privacy Protection. International Journal of Computer Applications. 117, 6 ( May 2015), 1-6. DOI=10.5120/20555-2935

@article{ 10.5120/20555-2935,
author = { Anuradha K. Kudlikar, Meghana B. Nagori },
title = { Refinement in Personalize Web Search System with Privacy Protection },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 6 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume117/number6/20555-2935/ },
doi = { 10.5120/20555-2935 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:58:33.910361+05:30
%A Anuradha K. Kudlikar
%A Meghana B. Nagori
%T Refinement in Personalize Web Search System with Privacy Protection
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 6
%P 1-6
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

There are number of users searching for particular information with same topic. Personalized web search helps to improve the excellence of various searches on the Internet. But during searching the search engine may disclose or use user's personal information to improve search performance. We propose a fine tuning in Personalize Web Search system by generalizing user profiles. We suggest a technique to generate online profile with user's permission for query. Every time when user requests for certain information ,our system allows user to select profile information as per his or her requirement and risk of exposition of sensitive attributes such as name ,gender, contact number and many other different attributes. In addition our systems will also help to search accurate information based on user interests. Thus this system maintains stability between use of personalize information and the risk of exposing of personal profile by refining profile. This system is developed by GreedyIL algorithm which improves search quality and makes search computation fast

References
  1. Google personalized search: http://www. Google. com/psearch
  2. Yahoo! My Web 2. 0: http://myweb2. search. yahoo. com/
  3. J. Pitkow, H. Schuetze, T. Cass, R. Cooley, D. Turnbull, A. Edmonds, E. Adar, and T. Breuel, 2002. Personalized search. Communications of the ACM, 45(9):50-55.
  4. Z. Dou, R. Song, and J. -R. Wen 2007. A Large-Scale Evaluation and Analysis of Personalized Search Strategies. Proc. Int'l Conf. World Wide Web (WWW), pp. 581-590.
  5. J. Teevan, S. T. Dumais, and E. Horvitz 2005. 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.
  6. M. Spertta and S. Gach 2005. Personalizing Search Based on User Search Histories. Proc. IEEE/WIC/ACM Int'l Conf. Web Intelligence (WI).
  7. B. Tan, X. Shen, and C. Zhai 2006. Mining Long-Term Search History to Improve Search Accuracy. Proc. ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD).
  8. K. Sugiyama, K. Hatano, and M. Yoshikawa 2004. Adaptive Web Search Based on User Profile Constructed without any Effort from Users. Proc. 13th Int'l Conf. World Wide Web (WWW).
  9. X. Shen, B. Tan, and C. Zhai 2005. Implicit User Modeling for Personalized Search. Proc. 14th ACM Int'l Conf. Information and Knowledge Management (CIKM) .
  10. X. Shen, B. Tan, and C. Zhai 2005. Context-Sensitive Information Retrieval Using Implicit Feedback. Proc. 28th Ann. Int'l ACMSIGIR Conf. Research and Development Information Retrieval (SIGIR).
  11. F. Qiu and J. Cho 2006. Automatic Identification of User Interest for Personalized Search. Proc. 15th Int'l Conf. World Wide Web (WWW), pp. 727-736.
  12. Y. Xu, K. Wang, B. Zhang, and Z. Chen 2007. Privacy-Enhancing Personalized Web Search. Proc. 16th Int'l Conf. World Wide Web (WWW), pp. 591-600. A. Krause and E. Horvitz 2010. A Utility Theoretic Approach to Privacy in Online Services. J. Artificial Intelligence Research, vol. 39, pp. 633-662.
  13. J. S. Breese, D. Heckerman, and C. M. Kadie 1998. Empirical Analysis of Predictive Algorithms for Collaborative Filtering. Proc. 14th Conference Uncertainty in Artificial Intelligence (UAI), pp. 43-52, 1998.
  14. P. Yuvasri S. Boopathy 2013. Performance Analysis on Direct and Indirect Discrimination in Data Mining. International Journal of Advanced Research in Computer Science and Software Engineering Volume 3, Issue 11, ISSN: 2277 128X.
  15. Lidan Shou, He Bai, Ke Chen, and Gang Chen 2014. Supporting Privacy Protection in Personalized Web Search. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING VOL: 26 NO:2.
Index Terms

Computer Science
Information Sciences

Keywords

Personalize web search profile generalization Greedy algorithm discrimination power information loss.

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