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Joint Learning for Aspect and Polarity Classification in Persian Reviews Using Multi-Task Deep Learning

2022-01-17 09:54:35
Milad Vazan
arXiv_CL
             
Abstract

The purpose of this paper focuses on two sub-tasks related to aspect-based sentiment analysis, namely, aspect category detection (ACD) and aspect category polarity (ACP) in the Persian language. Most of the previous methods only focus on solving one of these sub-tasks separately. In this paper, we propose a multi-task learning model based on deep neural networks, which can concurrently detect aspect category and detect aspect category polarity. We evaluated the proposed method using a Persian language dataset in the movie domain on different deep learning-based models. Final experiments show that the CNN model has better results than other models.

Abstract (translated)

URL

https://arxiv.org/abs/2201.06313

PDF

https://arxiv.org/pdf/2201.06313.pdf

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