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2007
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Information flow modeling based on diffusion rate for prediction and ranking

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Information flow modeling based on diffusion rate for prediction and ranking
Information flows in a network where individuals influence each other. The diffusion rate captures how efficiently the information can diffuse among the users in the network. We propose an information flow model that leverages diffusion rates for: (1) prediction ? identify where information should flow to, and (2) ranking ? identify who will most quickly receive the information. For prediction, we measure how likely information will propagate from a specific sender to a specific receiver during a certain time period. Accordingly a rate-based recommendation algorithm is proposed that predicts who will most likely receive the information during a limited time period. For ranking, we estimate the expected time for information diffusion to reach a specific user in a network. Subsequently, a DiffusionRank algorithm is proposed that ranks users based on how quickly information will flow to them. Experiments on two datasets demonstrate the effectiveness of the proposed algorithms to both imp...
Xiaodan Song, Yun Chi, Koji Hino, Belle L. Tseng
Added 22 Nov 2009
Updated 22 Nov 2009
Type Conference
Year 2007
Where WWW
Authors Xiaodan Song, Yun Chi, Koji Hino, Belle L. Tseng
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