slugPrediction of Concealed Information from Social Networks
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2014, Vol 2, Issue 3
Abstract
The online applications like social networks that allow the users to connect each other by different links. The users can update their profile with information of their friends and their private information. Some of their private information has higher possibilities to predict the private information from the user’s information using some learning algorithms. To reduce accuracy of the profile, three refinement techniques are created which is used in various situations and the effectiveness of these techniques are explored. These techniques remove the details and friendship links together. This is the best way to reduce classifier accuracy. This method is probably infeasible in maintaining the use of social networks. Naive Bayes algorithm is used to gives the maximum accuracy that is able to find the classifier of a profile. The objective is to reduce the classifier accuracy, while the details and the friendship links are removed together.
Authors and Affiliations
R. Shiny Jenita, J. A. M. Rexie
Keywords
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