SEML: A Semi-Supervised Multi-Task Learning Framework for Aspect-Based Sentiment Analysis

SEML: A Semi-Supervised Multi-Task Learning Framework for Aspect-Based Sentiment Analysis

Aspect-Based Sentiment Analysis (ABSA) involves two sub-tasks, namely Aspect Mining (AM) and Aspect Sentiment Classification (ASC), which aims to extract the words describing aspects of a reviewed entity (e.g., a product or service) and analyze the expressed sentiments on the aspects. As AM and ASC...

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Bibliographic Details
Main Authors: Ning Li, Chi-Yin Chow, Jia-Dong Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Aspect-based sentiment analysis
semi-supervised learning
multi-task learning
end-to-end learning
cross-view training
moving-window attention
Online Access:https://ieeexplore.ieee.org/document/9226421/

Internet

https://ieeexplore.ieee.org/document/9226421/

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