Comprehensive Analysis of Aspect Term Extraction Methods using Various Text Embeddings

@article{Augustyniak2021ComprehensiveAO,
  title={Comprehensive Analysis of Aspect Term Extraction Methods using Various Text Embeddings},
  author={Lukasz Augustyniak and Tomasz Kajdanowicz and Przemysław Kazienko},
  journal={Comput. Speech Lang.},
  year={2021},
  volume={69},
  pages={101217}
}
Recently, a variety of model designs and methods have blossomed in the context of the sentiment analysis domain. However, there is still a lack of wide and comprehensive studies of aspect-based sentiment analysis (ABSA). We want to fill this gap and propose a comparison with ablation analysis of aspect term extraction using various text embedding methods. We particularly focused on architectures based on long short-term memory (LSTM) with optional conditional random field (CRF) enhancement… Expand
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References

SHOWING 1-10 OF 76 REFERENCES
Unsupervised Word and Dependency Path Embeddings for Aspect Term Extraction
Aspect extraction for opinion mining with a deep convolutional neural network
Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction
Dependency-Tree Based Convolutional Neural Networks for Aspect Term Extraction
DLIREC: Aspect Term Extraction and Term Polarity Classification System
Multi-aspect Sentiment Analysis with Topic Models
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