Finding web appearances of social network users via latent factor model
Kailong Chen, Zhengdong Lu, Xiaoshi Yin, Yong Hai Yu, Zaiqing Nie · 2012
With the rapid growing of Web 2.0, people spend more time on social networks such as Facebook and Twitter. In order to know the people they are interacting with, finding the web appearances of them will help the social network users to a great extent. We propose a novel and effective latent factor model to find web appearances of target social network users. Our method solves the name ambiguity problem by simultaneously exploring the link structure of social networks and the web. Experiments on real-world data show the superiority of our method over several baselines.