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Interpretable Semantic Vectors from a Joint Model of Brain- and Text-Based Meaning
Vector space models (VSMs) represent word meanings as points in a high dimensional space. VSMs are typically created using a large text corpora, and so represent word semantics as observed in text. We present a new algorithm (JNNSE) that can incorporate a measure of semantics not previously used to...
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| Publicado no: | Proc Conf Assoc Comput Linguist Meet |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2014
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4497373/ https://ncbi.nlm.nih.gov/pubmed/26166940 |
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