Enhancing Attention-Based LSTM With Position Context for Aspect-Level Sentiment Classification

Enhancing Attention-Based LSTM With Position Context for Aspect-Level Sentiment Classification

Aspect-level sentiment classification is an interesting but challenging research problem, namely, the prediction of the sentiment polarity toward a specific aspect term of an opinionated sentence. Previous attention-based recurrent neural networks have been proposed to address this problem because a...

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Bibliographic Details
Main Authors: Jiangfeng Zeng, Xiao Ma, Ke Zhou
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Data analysis
natural language processing
sentiment classification
aspect-level
recurrent neural networks
long short-term memory
Online Access:https://ieeexplore.ieee.org/document/8631132/

Internet

https://ieeexplore.ieee.org/document/8631132/

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