【摘 要】
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Link prediction problems aim to predict potential edges which will occur in the future time,or the ``missing links that arent detected at the present in the network.Many researches have made efforts t
【机 构】
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College of Engineering & Information Technology,University of ChineseAcademy of Sciences,China
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Link prediction problems aim to predict potential edges which will occur in the future time,or the ``missing links that arent detected at the present in the network.Many researches have made efforts to improve the performance of the link prediction problem,ranging from methods relying on the graph structure to methods depending on attributes data.However,the research of how to effectively combine the structural properties with rich node and edge attributes data remains an open problem.In this talk,we propose a new similarity measure,and provide a novel approach to introduce Bayesian method naturally supervising the transitivity process,which makes best use of the structural transitivity scheme and node attribute together.
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