Vol. 9 Issue 4
Year:2015
Issue:Apr-Jun
Title:Evaluating the Privacy of User Profiles in Personalized Information Systems
Author Name:U. Yobu and B. Lalitha
Synopsis:
Collaborative tagging is one of the most well-known and widespread services available online. The key point of collaborative tagging is to distinguish the resources based on user opinion, stated in the form of tags. Collaborative tagging supplies the source for the semantic Web, network will connect all online resources based on their meanings. While this information is a valued source, its total volume limits its value. Most of the research projects and corporations are discovering the use of personalized applications that control this overflow by modifying the information obtainable to individual users. These applications altogether utilize some information about individuals in directive to be active. This zone is generally called user profiling. In this paper some of the most standard techniques for gathering information about users, signifying, and constructing user profiles. This paper mainly focus on measuring the privacy of user profiles through kl divergence and Shannon entropy techniques showing the tag suppression that protects the end user privacy.
Year:2015
Issue:Apr-Jun
Title:Evaluating the Privacy of User Profiles in Personalized Information Systems
Author Name:U. Yobu and B. Lalitha
Synopsis:
Collaborative tagging is one of the most well-known and widespread services available online. The key point of collaborative tagging is to distinguish the resources based on user opinion, stated in the form of tags. Collaborative tagging supplies the source for the semantic Web, network will connect all online resources based on their meanings. While this information is a valued source, its total volume limits its value. Most of the research projects and corporations are discovering the use of personalized applications that control this overflow by modifying the information obtainable to individual users. These applications altogether utilize some information about individuals in directive to be active. This zone is generally called user profiling. In this paper some of the most standard techniques for gathering information about users, signifying, and constructing user profiles. This paper mainly focus on measuring the privacy of user profiles through kl divergence and Shannon entropy techniques showing the tag suppression that protects the end user privacy.
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