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Semi-Supervised Learning of Statistical Models for Natural Language Understanding
Natural language understanding is to specify a computational model that maps sentences to their semantic mean representation. In this paper, we propose a novel framework to train the statistical models without using expensive fully annotated data. In particular, the input of our framework is a set o...
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| Hlavní autoři: | , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Hindawi Publishing Corporation
2014
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4127215/ https://ncbi.nlm.nih.gov/pubmed/25152899 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2014/121650 |
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