Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/65115
Título: | Machine learning algorithms and techniques for sentiment analysis in scientific paper reviews: a systematic literature review |
Autor(es): | Machado, Samuel Ribeiro, Ana Carolina Freitas Oliveira e Sá, Jorge |
Palavras-chave: | Machine Learning Sentiment Analysis Opinion Mining Systematic Literature Review |
Data: | 2019 |
Editora: | Associação Portuguesa de Sistemas de Informação (APSI) |
Revista: | Atas da Conferência da Associação Portuguesa de Sistemas de Informação |
Citação: | S. Machado, A. C. Ribeiro, and J. O. e Sá, “Machine Learning Algorithms and Techniques for Sentiment Analysis in Scientific Paper Reviews : A Systematic Literature Review,” in 19a Conferência da Associação Portuguesa de Sistemas de Informação, 2019. |
Resumo(s): | Sentiment analysis also referred to as opinion mining, is an automated process for identifying and classifying subjective information such as sentiments from a piece of text usually comments and reviews. Supported by machine learning algorithms, it is possible to identify positive, neutral or negative opinions, being possible to rank or classify them in order to reach some kind of conclusion or obtain any type of information. Thus, this paper aims to perform a systematic literature review in order to report the state-of-the-art of machine learning techniques for sentiment analysis applied to texts of reviews, comments and evaluations of scientific papers. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/65115 |
ISSN: | 2183-489X |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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CAPSI_revisões_final.pdf | 384,15 kB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons