| Autor: |
Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., Pavel Kuksa |
| Jazyk: |
angličtina |
| Rok vydání: |
2011 |
| Předmět: |
|
| Zdroj: |
Scopus-Elsevier |
| Popis: |
We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including: part-of-speech tagging, chunking, named entity recognition, and semantic role labeling. This versatility is achieved by trying to avoid task-specific engineering and therefore disregarding a lot of prior knowledge. Instead of exploiting man-made input features carefully optimized for each task, our system learns internal representations on the basis of vast amounts of mostly unlabeled training data. This work is then used as a basis for building a freely available tagging system with good performance and minimal computational requirements. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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