| Autor: |
Memari, Mohammadali, Nejad, Soghra Mikaeyl, Rabiei, Amir Parsa, Eisaei, Mehrshad, Hesaraki, Saba |
| Rok vydání: |
2024 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
Multidomain sentiment analysis involves estimating the polarity of an unstructured text by exploiting domain specific information. One of the main issues common to the approaches discussed in the literature is their poor applicability to domains that differ from those used to construct opinion models.This paper aims to present a new method for Persian multidomain SA analysis using deep learning approaches. The proposed BERTCapsules approach consists of a combination of BERT and Capsule models. In this approach, BERT was used for Instance representation, and Capsule Structure was used to learn the extracted graphs. Digikala dataset, including ten domains with both positive and negative polarity, was used to evaluate this approach. The evaluation of the BERTCaps model achieved an accuracy of 0.9712 in sentiment classification binary classification and 0.8509 in domain classification . |
| Databáze: |
arXiv |
| Externí odkaz: |
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