PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks

@article{Tang2015PTEPT,
  title={PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks},
  author={Jian Tang and Meng Qu and Q. Mei},
  journal={ArXiv},
  year={2015},
  volume={abs/1508.00200}
}
  • Jian Tang, Meng Qu, Q. Mei
  • Published 2015
  • Computer Science
  • ArXiv
  • Unsupervised text embedding methods, such as Skip-gram and Paragraph Vector, have been attracting increasing attention due to their simplicity, scalability, and effectiveness. However, comparing to sophisticated deep learning architectures such as convolutional neural networks, these methods usually yield inferior results when applied to particular machine learning tasks. One possible reason is that these text embedding methods learn the representation of text in a fully unsupervised way… CONTINUE READING
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