Valéria Delisandra Feltrim

Also published as: Valéria D. Feltrim, Valéria Feltrim


2015

pdf
Análise Automática de Coerência Textual em Resumos Científicos: Avaliando Quebras de Linearidade (Automatic Analysis of Textual Coherence in Scientific Abstracts: Evaluating Linearity Breaks)
Leandro Lago da Silva | Valéria Delisandra Feltrim
Proceedings of the 10th Brazilian Symposium in Information and Human Language Technology

pdf
Extração de Alvos em Comentários de Notícias em Português baseada na Teoria da Centralização (Target Extraction in News Reviews in Portuguese based on Centering Theory)
Frank Willian Cardoso de Oliveira | Valéria Delisandra Feltrim
Proceedings of the 10th Brazilian Symposium in Information and Human Language Technology

pdf
Campos Aleatórios Condicionais Aplicados à Detecção de Estrutura Retórica em Resumos de Textos Acadêmicos em Português (Conditional Random Fields Applied to Rhetorical Structure Detection in Academic Abstracts in Portuguese)
Alexandre C. Andreani | Valéria D. Feltrim
Proceedings of the 10th Brazilian Symposium in Information and Human Language Technology

2013

pdf
Uma Investigação sobre Algoritmos de Diferentes Abordagens de Aprendizado Supervisionado na Classificação de Papéis Retóricos em Resumos Científicos (Investigating Algorithms from Different Approaches of Supervised Learning for the Classification of Rhetorical Roles in Scientific Abstracts) [in Portuguese]
Vinícius M. A. de Souza | Valéria D. Feltrim
Proceedings of the 9th Brazilian Symposium in Information and Human Language Technology

pdf
Análise Automática de Coerência Usando o Modelo Grade de Entidades para o Português (Automatic Coherence Analysis Using the Entity-grid Model for Portuguese) [in Portuguese]
Alison R. P. Freitas | Valéria D. Feltrim
Proceedings of the 9th Brazilian Symposium in Information and Human Language Technology

2012

pdf
Rhetorical Move Detection in English Abstracts: Multi-label Sentence Classifiers and their Annotated Corpora
Carmen Dayrell | Arnaldo Candido Jr. | Gabriel Lima | Danilo Machado Jr. | Ann Copestake | Valéria Feltrim | Stella Tagnin | Sandra Aluisio
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

The relevance of automatically identifying rhetorical moves in scientific texts has been widely acknowledged in the literature. This study focuses on abstracts of standard research papers written in English and aims to tackle a fundamental limitation of current machine-learning classifiers: they are mono-labeled, that is, a sentence can only be assigned one single label. However, such approach does not adequately reflect actual language use since a move can be realized by a clause, a sentence, or even several sentences. Here, we present MAZEA (Multi-label Argumentative Zoning for English Abstracts), a multi-label classifier which automatically identifies rhetorical moves in abstracts but allows for a given sentence to be assigned as many labels as appropriate. We have resorted to various other NLP tools and used two large training corpora: (i) one corpus consists of 645 abstracts from physical sciences and engineering (PE) and (ii) the other corpus is made up of 690 from life and health sciences (LH). This paper presents our preliminary results and also discusses the various challenges involved in multi-label tagging and works towards satisfactory solutions. In addition, we also make our two training corpora publicly available so that they may serve as benchmark for this new task.

2011

pdf
Automatic Analysis of Semantic Coherence in Academic Abstracts Written in Portuguese
Vinícius Mourão Alves de Souza | Valéria Delisandra Feltrim
Proceedings of 5th International Joint Conference on Natural Language Processing

pdf
Análise automática de aspectos relacionados a coerência semântica em resumos acadêmicos (Automatic Analysis of Semantic Coherence Aspects in Academic Abstracts) [in Portuguese]
Vinícius Mourão Alves de Souza | Valéria Delisandra Feltrim
Proceedings of the 8th Brazilian Symposium in Information and Human Language Technology