Link prediction in online social networks based on supervised joint denoising model

@inproceedings{Hao2017LinkPI,
  title={Link prediction in online social networks based on supervised joint denoising model},
  author={Zhangang Hao and Weixiong Zhang and Zhigang Chen},
  year={2017}
}
Link prediction of social networks can capture important information about missing links for applications in many fields. Because of the failure to make full use of information as well as capture all properties, the link prediction precision of most of methods is low. For higher precision, we propose a novel algorithm, a supervised joint denoising model (SJDM) that formulates the link prediction problem as a supervised matrix “denoising problem. The central piece of our method is a function… CONTINUE READING

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