Rafael Anchiêta


2024

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A Reproducibility Analysis of Portuguese Computational Processing Conferences: A Case of Study
Daniel Leal | Anthony Luz | Rafael Anchiêta
Proceedings of the 16th International Conference on Computational Processing of Portuguese

2021

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A Semi-Supervised Approach to Detect Toxic Comments
Ghivvago Damas Saraiva | Rafael Anchiêta | Francisco Assis Ricarte Neto | Raimundo Moura
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)

Toxic comments contain forms of non-acceptable language targeted towards groups or individuals. These types of comments become a serious concern for government organizations, online communities, and social media platforms. Although there are some approaches to handle non-acceptable language, most of them focus on supervised learning and the English language. In this paper, we deal with toxic comment detection as a semi-supervised strategy over a heterogeneous graph. We evaluate the approach on a toxic dataset of the Portuguese language, outperforming several graph-based methods and achieving competitive results compared to transformer architectures.

2020

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Semantically Inspired AMR Alignment for the Portuguese Language
Rafael Anchiêta | Thiago Pardo
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Abstract Meaning Representation (AMR) is a graph-based semantic formalism where the nodes are concepts and edges are relations among them. Most of AMR parsing methods require alignment between the nodes of the graph and the words of the sentence. However, this alignment is not provided by manual annotations and available automatic aligners focus only on the English language, not performing well for other languages. Aiming to fulfill this gap, we developed an alignment method for the Portuguese language based on a more semantically matched word-concept pair. We performed both intrinsic and extrinsic evaluations and showed that our alignment approach outperforms the alignment strategies developed for English, improving AMR parsers, and achieving competitive results with a parser designed for the Portuguese language.

2018

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Towards AMR-BR: A SemBank for Brazilian Portuguese Language
Rafael Anchiêta | Thiago Pardo
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2017

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Improving Opinion Summarization by Assessing Sentence Importance in On-line Reviews
Rafael Anchiêta | Rogerio Figueredo Sousa | Raimundo Moura | Thiago Pardo
Proceedings of the 11th Brazilian Symposium in Information and Human Language Technology