Authors: Zhiqiang Wang, Jiye Liang, Ru Li, Yuhua Qian

Abstract:

Authors:Zhiqiang Wang, Jiye Liang, Ru Li, Yuhua Qian
Abstract:Cold-start link prediction is a term for information starved link prediction where little or no topological information is present to guide the determination of whether links to a node will form. Due to the lack of topological information, traditional topology-based link prediction methods cannot be applied to solve the cold-start link prediction problem. Therefore, an effective approach is presented through establishing connections between non-topological and topological information. In the approach, topological information is first extracted by a latent-feature representation model, then a logistic model is proposed to establish the connections between topological and non-topological information, and finally the linking possibility between cold-start users and existing users is calculated. Experiments with three types of real-world social networks Weibo, Facebook and Twitter show that the proposed approach is more effective in solving the cold-start link prediction problem and establishing connections between topological and non-topological information.
Index Terms—social network, link prediction, predictive model, latent feature
An approach to cold-start link prediction: establishing connections between non-topological and topological information

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an approach to cold-start link prediction-establishing connections between non-topological and topological information.pdf

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Sat Jul 02 00:00:00 CST 2016