Open AccessA Model for Predicting Human Depression using Machine Learning Algorithm
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.c1086.0193s20
Subject(s) - computer science , context (archaeology) , image sharing , the internet , access control , task (project management) , information privacy , internet privacy , social media , privacy policy , machine learning , image (mathematics) , data sharing , privacy software , control (management) , file sharing , world wide web , artificial intelligence , computer security , medicine , paleontology , alternative medicine , management , pathology , economics , biology
In recent days people share their images in many social media and also they are not certain about the privacy. This leads to many issues. In light of these incidents, a tool is needed for providing access control method during user’s file sharing. To do that, Adaptive Privacy Policy Prediction (A3P) system is proposed for setting the privacy parameters to their images. The image data, user’s social context and their meta data are used in the privacy setting preferences. The author proposed a two-stage framework for determining and setting the existing privacy policy in accordance to the user’s history over the website. The proposed solution depends on the image categories and the social features of the user. Also, it depends on the user’s privacy data and the relevant features. From the experimental and simulation results it is proved that the privacy preservation is one of the important task in internet applications.