Papers by Joaquim Santos
Word Embedding Evaluation in Downstream Tasks and Semantic Analogies (2020.lrec-1)
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| Challenge: | Language Models (LMs) are an oft studied area of natural language processing . Word Embeddings (WE) are vector space representations of a vocabulary . |
| Approach: | They evaluate Word Embeddings (WE) models for the Portuguese langauage . results show that a diverse corpus can often outperform a larger, less textually diverse corp. |
| Outcome: | The proposed models outperform a larger, less textually diverse corpus in two tasks . the evaluation shows that a diverse and comprehensive corpus outperformed a smaller, less diverse corp. |
Embeddings for Named Entity Recognition in Geoscience Portuguese Literature (2020.lrec-1)
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| Challenge: | Named Entity Recognition (NER) is a task within the field of Natural Language Processing that deals with the identification and categorization of Named entities (NEs) in a given text. |
| Approach: | They propose to use vector and tensor embeddings to train Portuguese Named Entity Recognition (NER) in the Geology domain. |
| Outcome: | The proposed model achieves state-of-the-art for the Portuguese Geology domain with one of its embeddings. |