期刊名称:International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN:2320-9798
电子版ISSN:2320-9801
出版年度:2016
卷号:4
期号:2
页码:2363
DOI:10.15680/IJIRCCE.2016.0402135
出版社:S&S Publications
摘要:SNSis a platform to constructsocial networks or social relations among people based on their social graph It is not satisfied to user's preference on friend selection in real life. Mean while in proposed system, we recommend friend by used semantic-based (or) user based on their lifestyle.By taking merits of sensor-rich Smartphone's, Friend matching graph find out something life styles of people from user-centric sensor data, action to achieve something the similarity of life styles between users, and to advise someone to users if their life styles have most similarity.An extra ordinary qualityby data mining, a user's daily life documents are extracted by using theHierarchical dirichlet algorithm. Pasta certain point, a similar metric to measure the similarity of life styles between users and enumerate therecommend user's the action of one object coming forcibly into contact with another. When receiving a request, it returns a list of social network user with highest recommendation scores to the query user. At last, Friend matching graph combine with another to form a whole the feedback mechanism to further improve the recommendation user accurate. We implemented on the Android-based Smartphone's, and its routineon both small-scale experiments and large-scale simulations. The results show that the recommendations defect reflects the preferences of users in choosing friends in social network