Search Results for author: r{\'e}

Found 18 papers, 0 papers with code

Searching Brazilian Twitter for Signs of Mental Health Issues

no code implementations LREC 2020 Wesley Santos, Am Funabashi, a, Iv Paraboni, r{\'e}

Depression and related mental health issues are often reflected in the language employed by the individuals who suffer from these conditions and, accordingly, research in Natural Language Processing (NLP) and related fields have developed an increasing number of studies devoted to their recognition in social media text.

Text Classification

Cross-domain Author Gender Classification in Brazilian Portuguese

no code implementations LREC 2020 Rafael Dias, Iv Paraboni, r{\'e}

Author profiling models predict demographic characteristics of a target author based on the text that they have written.

General Classification

Moral Stance Recognition and Polarity Classification from Twitter and Elicited Text

no code implementations RANLP 2019 Wesley Santos, Iv Paraboni, r{\'e}

We introduce a labelled corpus of stances about moral issues for the Brazilian Portuguese language, and present reference results for both the stance recognition and polarity classification tasks.

General Classification

Personality-dependent Neural Text Summarization

no code implementations RANLP 2019 Pablo Costa, Iv Paraboni, r{\'e}

In Natural Language Generation systems, personalization strategies - i. e, the use of information about a target author to generate text that (more) closely resembles human-produced language - have long been applied to improve results.

Abstractive Text Summarization Text Generation

Improving the generation of personalised descriptions

no code implementations WS 2017 Thiago Castro Ferreira, Iv Paraboni, r{\'e}

Referring expression generation (REG) models that use speaker-dependent information require a considerable amount of training data produced by every individual speaker, or may otherwise perform poorly.

Referring expression generation Text Generation

Corpus-based Referring Expressions Generation

no code implementations LREC 2012 Hilder Pereira, Eder Novais, Andr{\'e} Mariotti, Iv Paraboni, r{\'e}

In Natural Language Generation, the task of attribute selection (AS) consists of determining the appropriate attribute-value pairs (or semantic properties) that represent the contents of a referring expression.

Text Generation

Portuguese Text Generation from Large Corpora

no code implementations LREC 2012 Eder Novais, Iv Paraboni, r{\'e}, Douglas Silva

Among these, there is the issue of data sparseness, a problem that is particularly evident in cases such as our target language - Brazilian Portuguese - which is not only morphologically-rich, but relatively poor in NLP resources such as large, publicly available corpora.

Language Modelling Text Generation

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