Friend recommendation in social multimedia networks

With the rapid development of computer science and internet technologies, social media and social network has experienced explosive growth over the last decades. Social websites, such as Flickr, YouTube, and Twitter, have billions of users who share photos, videos and opinions, they also make friends on these websites. On-line friendship is an emerging topic that attracts the attentions from both economists and sociologists. The study of the on-line friendship, on one hand, can help the on-line merchants to find their potential customers, and thus make more precise recommendations; on the other hand, it helps to get a deep understanding of the relationships among different people. However, individuals’ on-line friend making behaviour is relatively complex and may be affected by many different factors. For example, an individual might make on-line friends with others because they discuss a hard mathematical problem, or it is possible that he/she makes a friend because they both enjoy a film. The reasons for friend making behaviours are likely to be diverse. Traditional friend recommendations that have been widely applied by Facebook and Twitter are often based on common friends and similar profiles such as having the same hobbies or working on a similar topic, which usually can not make a precise recommendation, due to the complexity of the problem. In this thesis, I, with my collaborators, try to give some solutions of on-line social friend recommendation from several aspects. In general, I contribute more than 85% of this thesis. One problem for social friend recommendation is that how shall we find the important social features that would highly influence individuals’ friend

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