The objective of the Personalized web search (PWS) is to provide an effective and efficient search results, which are tailor mode for individual user needs. we build user profiles based on user preference and these profiles are then used to re-rank the search results and rank the order of user-examined results.User privacy can be protected without affecting the personalized search quality. However, users are troubled, with exposing personal preference information to search engines has become a major limitation for profile based personalized web search.The Privacy-preserving personalized web search framework is called UPS framework which can generalize profiles for each query according to user-specific privacy requirements. .In general, there is a tradeoff between the search quality and the level of privacy protection achieved from generalization. Effective generalization algorithms namely GreedyDP and GreedyIL are used to support the runtime profiling. Experiments are conducted on real web search data show that the algorithms are effective in enhancing the stability of the search quality and avoids the unnecessary exposure of the user profile.
%0 Journal Article
%1 Pradeep_2015
%A Pradeep, Prof. G.
%A Priyanga, E.
%A Durgadevi, M.
%A Kaviya, T.
%A Priyanka, A.
%D 2015
%I Auricle Technologies, Pvt., Ltd.
%J International Journal on Recent and Innovation Trends in Computing and Communication
%K Generalization Privacy Profile Rerank
%N 3
%P 1517--1520
%R 10.17762/ijritcc2321-8169.1503135
%T A Novel Framework For User Customizable Privacy Preserving Search
%U http://dx.doi.org/10.17762/ijritcc2321-8169.1503135
%V 3
%X The objective of the Personalized web search (PWS) is to provide an effective and efficient search results, which are tailor mode for individual user needs. we build user profiles based on user preference and these profiles are then used to re-rank the search results and rank the order of user-examined results.User privacy can be protected without affecting the personalized search quality. However, users are troubled, with exposing personal preference information to search engines has become a major limitation for profile based personalized web search.The Privacy-preserving personalized web search framework is called UPS framework which can generalize profiles for each query according to user-specific privacy requirements. .In general, there is a tradeoff between the search quality and the level of privacy protection achieved from generalization. Effective generalization algorithms namely GreedyDP and GreedyIL are used to support the runtime profiling. Experiments are conducted on real web search data show that the algorithms are effective in enhancing the stability of the search quality and avoids the unnecessary exposure of the user profile.
@article{Pradeep_2015,
abstract = {The objective of the Personalized web search (PWS) is to provide an effective and efficient search results, which are tailor mode for individual user needs. we build user profiles based on user preference and these profiles are then used to re-rank the search results and rank the order of user-examined results.User privacy can be protected without affecting the personalized search quality. However, users are troubled, with exposing personal preference information to search engines has become a major limitation for profile based personalized web search.The Privacy-preserving personalized web search framework is called UPS framework which can generalize profiles for each query according to user-specific privacy requirements. .In general, there is a tradeoff between the search quality and the level of privacy protection achieved from generalization. Effective generalization algorithms namely GreedyDP and GreedyIL are used to support the runtime profiling. Experiments are conducted on real web search data show that the algorithms are effective in enhancing the stability of the search quality and avoids the unnecessary exposure of the user profile.},
added-at = {2015-08-13T07:16:36.000+0200},
author = {Pradeep, Prof. G. and Priyanga, E. and Durgadevi, M. and Kaviya, T. and Priyanka, A.},
biburl = {https://www.bibsonomy.org/bibtex/28e4d36fa482ede3f6dc0a9fec74e56cb/ijritcc},
doi = {10.17762/ijritcc2321-8169.1503135},
interhash = {fc04cd9497cd723f10c70ddef896da20},
intrahash = {8e4d36fa482ede3f6dc0a9fec74e56cb},
journal = {International Journal on Recent and Innovation Trends in Computing and Communication},
keywords = {Generalization Privacy Profile Rerank},
month = {march},
number = 3,
pages = {1517--1520},
publisher = {Auricle Technologies, Pvt., Ltd.},
timestamp = {2015-08-13T07:16:36.000+0200},
title = {A Novel Framework For User Customizable Privacy Preserving Search},
url = {http://dx.doi.org/10.17762/ijritcc2321-8169.1503135},
volume = 3,
year = 2015
}