Diffusion Maps for Textual Network Embedding

@inproceedings{Zhang2018DiffusionMF,
  title={Diffusion Maps for Textual Network Embedding},
  author={Xinyuan Zhang and Yitong Li and Dinghan Shen and Lawrence Carin},
  booktitle={NeurIPS},
  year={2018}
}
Textual network embedding leverages rich text information associated with the network to learn low-dimensional vectorial representations of vertices. Rather than using typical natural language processing (NLP) approaches, recent research exploits the relationship of texts on the same edge to graphically embed text. However, these models neglect to measure the complete level of connectivity between any two texts in the graph. We present diffusion maps for textual network embedding (DMTE… CONTINUE READING
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