A unified architecture for natural language processing: deep neural networks with multitask learning

@inproceedings{Collobert2008AUA,
  title={A unified architecture for natural language processing: deep neural networks with multitask learning},
  author={Ronan Collobert and J. Weston},
  booktitle={ICML '08},
  year={2008}
}
We describe a single convolutional neural network architecture that, given a sentence, outputs a host of language processing predictions: part-of-speech tags, chunks, named entity tags, semantic roles, semantically similar words and the likelihood that the sentence makes sense (grammatically and semantically) using a language model. The entire network is trained jointly on all these tasks using weight-sharing, an instance of multitask learning. All the tasks use labeled data except the language… Expand
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References

SHOWING 1-6 OF 6 REFERENCES
A Neural Probabilistic Language Model
  • 4,925
  • Highly Influential
  • PDF
The Proposition Bank: An Annotated Corpus of Semantic Roles
  • 2,281
  • Highly Influential
  • PDF
Probabilistic Interpretation of Feedforward Classification Network Outputs, with Relationships to Statistical Pattern Recognition
  • J. Bridle
  • Computer Science
  • NATO Neurocomputing
  • 1989
  • 998
  • Highly Influential
Shallow Semantic Parsing using Support Vector Machines
  • 433
  • Highly Influential
  • PDF
Using Corpus Statistics on Entities to Improve Semi-supervised Relation Extraction from the Web
  • 51
  • Highly Influential
  • PDF
A neural probabilistic language model. NIPS 13
  • A neural probabilistic language model. NIPS 13
  • 2001