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Research Article Open Access
Social network sites attracted millions of users. In the social network sites, a user can register other users as friends and enjoy communication. Existing social networking sites recommend friends to users based on their social graphs, which may not be appropriate. In proposed system friends recommends to users based on their life styles instead of social graphs. It done by means of sensor rich smart- phone serve as the ideal platform for sensing daily routines from which people’s life styles could be discovered. Unsupervised learning method is used. Achieve an efficient activity Recognition and reduce the false positive of Friend Recommendation. Friendbook integrates a feedback mechanism. Finally the results show that the recommendations accurately reflect the preferences of users in choosing friends.
Friend book, Recommendation, Social network, Lifestyle., Aeronautics, Telecommunications, Metallurgy, Medical Electronics, Mechanical engineering, Mathematics and Statistics, Industrial Production,Environmental Engineering, Engineering Physics, Engineering Aspects Associated With Biotechnology, Electronics, Electrical engineering, Earth and Atmospheric Sciences, Computer Science and Information Technology, Civil and Architecture Engineering, Chemical Engineering, Biomedical Engineering, Bioinformatics, Textile and Polymer Engineering