Papers by Renata Vieira
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. |
BRATECA (Brazilian Tertiary Care Dataset): a Clinical Information Dataset for the Portuguese Language (2022.lrec-1)
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Bernardo Consoli, Henrique D. P. dos Santos, Ana Helena D. P. S. Ulbrich, Renata Vieira, Rafael H. Bordini
| Challenge: | Existing clinical datasets are in the English language and were collected in anglophone countries. |
| Approach: | They propose to use a Brazilian clinical dataset with over 2.5 million free-text clinical notes alongside data pertaining to patient information, prescription information, and exam results. |
| Outcome: | The Brazilian Clinical Dataset contains over 70,000 admissions from 10 hospitals in two Brazilian states. |
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. |
BlogSet-BR: A Brazilian Portuguese Blog Corpus (L18-1)
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| Challenge: | Several efforts have been made to build a corpus based on user-generated content . however, there is still a lack of a large semi-structured corpus that also contains author profiles in Brazilian Portuguese. |
| Approach: | They propose to build a Brazilian Portuguese corpus with 2.1 billion words extracted from 7.4 million posts over 808 thousand different Brazilian blogs. |
| Outcome: | The proposed corpus contains 2.1 billion words extracted from 7.4 million posts over 808 thousand different Brazilian blogs. |