# Controlled CNN-based Sequence Labeling for Aspect Extraction

arXiv: https://arxiv.org/abs/1905.06407 · HTML: https://mlsanity.com/paper/1905.06407/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 May 2019.

## Built on by (most cited first, 2 of 2)

- [Zero-Shot Aspect-Based Sentiment Analysis](https://mlsanity.com/paper/2202.01924/) (2022)
- [A Weak Supervision Approach for Few-Shot Aspect Based Sentiment](https://mlsanity.com/paper/2305.11979/) (2023)

## 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.