Controlled CNN-based Sequence Labeling for Aspect Extraction
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Abstract (arXiv)
One key task of fine-grained sentiment analysis on reviews is to extract aspects or features that users have expressed opinions on. This paper focuses on supervised aspect extraction using a modified CNN called controlled CNN (Ctrl). The modified CNN has two types of control modules. Through asynchronous parameter updating, it prevents over-fitting and boosts CNN's performance significantly. This model achieves state-of-the-art results on standard aspect extraction datasets. To the best of our knowledge, this is the first paper to apply control modules to aspect extraction.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 May 2019.
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Citing papers per year: 2022: 1; 2023: 1.
2 papers.
- 2022Zero-Shot Aspect-Based Sentiment Analysiscited by 5
- 2023A Weak Supervision Approach for Few-Shot Aspect Based Sentimentcited by 1
- 2023A Weak Supervision Approach for Few-Shot Aspect Based Sentiment19 May 2023
- 2022Zero-Shot Aspect-Based Sentiment Analysis4 Feb 2022