Recommendation in Social Website: A Method Based on Social Learning and the Strength of Ties

Fang-Fang MENG, Xiao ZHANG, Fang FANG


In this paper, a method based on the strength of ties and the social learning for online reviews to recommend products to a consumer. The strength of ties between the consumer and each of his friends are firstly calculated based on the background of the consumer’s friends. Then, the ratings of the products are obtained based on social learning and the strength of ties. Further, according to the ratings of products and the weights of the products attributes, the overall utilities of the products and a ranking of the products are determined. Finally, we propose a computational experiment to explain the proposed method.


Social Learning, Online Reviews, Ties, Recommendation


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