Exploração do uso de expressões do domínio na classificação de sentimentos
Abstract
Sentiment classification is an text mining application presents great challenges, requiring an adequate treatment of the textual semantic. In this work are presented the results of an experimental evaluation of a sentiment classification method for sentiment classification improvement that uses semantically enriched information. Such representation is built based on domain expressions, providing its interpretability and explainability. The results indicate that the method is promising, increasing accuracy values for databases with more concentrated information on a specific subject or domain.References
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Goodman, B. and Flaxman, S. (2017). European union regulations on algorithmic decision making and a "right to explanation". AI Magazine, 38(3):50–57.
Hu, M. and Liu, B. (2004). Mining and summarizing customer reviews. In 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 168–177.
Ju, H. and Yu, H. (2018). Sentiment Classication with Convolutional Neural Network using Multiple Word Representations. In 12th Int. Conf. on Ubiquitous Information Management and Communication, pages 1–7.
Liu, B. (2012). Sentiment Analysis and Opinion Mining. Morgan & Claypool Publishers. Pontiki, M., Galanis, D., Androutsopoulos, I., Manandhar, S., and Papageorgiou, H. (2014). SemEval-2014 Task 4: Aspect Based Sentiment Analysis. In 8th International Workshop on Semantic Evaluation, pages 27–35.
Pontiki, M., Galanis, D., Papageorgiou, H., Manandhar, S., and Androutsopoulos, I. (2015). Semeval-2015 task 12: Aspect based sentiment analysis. In 9th International Workshop on Semantic Evaluation, pages 486–495.
Scheicher, R. B., Sinoara, R. A., Felinto, J. C., and Rezende, S. O. (2019). Sentiment In 19th ACM classication improvement using semantically enriched information. Symposium on Document Engineering, pages 1–4.
Scheicher, R. B., Sinoara, R. A., Koga, N. J., and Rezende, S. O. (2016). Uso de expressões do domínio na classicação automática de documentos. Nacional de Inteligência Articial e Computacional, pages 625 – 636.
Xiong, S. (2016). Improving twitter sentiment classication via multi-level sentiment-enriched word embeddings.
Published
2020-08-19
How to Cite
SCHICHER, Ricardo; SINOARA, Roberta; REZENDE, Solange.
Exploração do uso de expressões do domínio na classificação de sentimentos. In: REGIONAL SCHOOL OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING, 1. , 2020, São Paulo.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
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p. 38-42.
