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Video recommendation is an important tool to help people access interesting videos. In this paper, we propose a universal scheme to integrate rich information for personalized video recommendation. Our approach regards video recommendation as a ranking task. First, it generates multiple ranking lists by exploring different information sources. In particular, one novel source user's relationship strength is inferred through the online social network and applied to recommend videos. Second, baseddoi:10.1007/s00530-012-0267-z fatcat:vu2jxkwobjcshf3evbf4pxwxle