Unsupervised Domain Adaptation via Weighted Sequential Discriminative Feature Learning for Sentiment Analysis

Unsupervised Domain Adaptation via Weighted Sequential Discriminative Feature Learning for Sentiment Analysis

Unsupervised domain adaptation (UDA) presents a significant challenge in sentiment analysis, especially when faced with differences between source and target domains. This study introduces Weighted Sequential Unsupervised Domain Adaptation (WS-UDA), a novel sequential framework aimed at discovering...

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Bibliographic Details
Main Authors: Haidi Badr, Nayer Wanas, Magda Fayek
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Applied Sciences
Subjects:
unsupervised domain adaptation
poor target resources
text classification
transfer learning
Online Access:https://www.mdpi.com/2076-3417/14/1/406

Internet

https://www.mdpi.com/2076-3417/14/1/406

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