Discriminative Relational Topic Models

@article{Chen2015DiscriminativeRT,
  title={Discriminative Relational Topic Models},
  author={Ning Chen and Jun Zhu and Fei Xia and Bo Zhang},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2015},
  volume={37},
  pages={973-986}
}
Relational topic models (RTMs) provide a probabilistic generative process to describe both the link structure and document contents for document networks, and they have shown promise on predicting network structures and discovering latent topic representations. However, existing RTMs have limitations in both the restricted model expressiveness and incapability of dealing with imbalanced network data. To expand the scope and improve the inference accuracy of RTMs, this paper presents three… CONTINUE READING
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