Social networking sites (SNSs) first appeared in the mid-90s. In recent years, Web 2.0 technologies have made modern SNSs increasingly popular and easier to use, and social networking has expanded explosively across the web. Too many new users may cause the cold start problem. Users sign up on a SNS and discover they do not have any friends. In this paper, we investigate a new model to make friend recommendations. This model includes location check-in data as predictors and calculates users’ checkin histories--users’ life patterns--to make friend recommendations. The results of our experiment show that this novel model provides better performance in making friend recommendations.
Luo, Jiaxi; Sinha, Atish P.; and Zhao, Huimin, "Location-sensitive Friend Recommendations in Online Social Networks" (2020). PACIS 2020 Proceedings. 155.
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