# Aspect Category Detection via Topic-Attention Network

arXiv: https://arxiv.org/abs/1901.01183 · HTML: https://mlsanity.com/paper/1901.01183/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Jan 2019.

## Built on by (most cited first, 13 of 13)

- [A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challenges](https://mlsanity.com/paper/2203.01054/) (2022)
- [ASAP: A Chinese Review Dataset Towards Aspect Category Sentiment Analysis and Rating Prediction](https://mlsanity.com/paper/2103.06605/) (2021)
- [Multi-Label Few-Shot Learning for Aspect Category Detection](https://mlsanity.com/paper/2105.14174/) (2021)
- [Label-enhanced Prototypical Network with Contrastive Learning for Multi-label Few-shot Aspect Category Detection](https://mlsanity.com/paper/2206.13980/) (2022)
- [Exploring Conditional Text Generation for Aspect-Based Sentiment Analysis](https://mlsanity.com/paper/2110.02334/) (2021)
- [Label-Driven Denoising Framework for Multi-Label Few-Shot Aspect Category Detection](https://mlsanity.com/paper/2210.04220/) (2022)
- [Investigating Monolingual and Multilingual BERTModels for Vietnamese Aspect Category Detection](https://mlsanity.com/paper/2103.09519/) (2021)
- [Jointly Modeling Aspect and Polarity for Aspect-based Sentiment Analysis in Persian Reviews](https://mlsanity.com/paper/2109.07680/) (2021)
- [BERT-ASC: Auxiliary-Sentence Construction for Implicit Aspect Learning in Sentiment Analysis](https://mlsanity.com/paper/2203.11702/) (2022)
- [Few-Shot Multi-Label Aspect Category Detection Utilizing Prototypical Network with Sentence-Level Weighting and Label Augmentation](https://mlsanity.com/paper/2309.15588/) (2023)
- [A Deep Convolutional Neural Networks Based Multi-Task Ensemble Model for Aspect and Polarity Classification in Persian Reviews](https://mlsanity.com/paper/2201.06313/) (2022)
- [Supervised Gradual Machine Learning for Aspect Category Detection](https://mlsanity.com/paper/2404.05245/) (2024)
- [Label-Guided Prompt for Multi-label Few-shot Aspect Category Detection](https://mlsanity.com/paper/2407.20673/) (2024)

## Abstract (arXiv)

The e-commerce has started a new trend in natural language processing through sentiment analysis of user-generated reviews. Different consumers have different concerns about various aspects of a specific product or service. Aspect category detection, as a subtask of aspect-based sentiment analysis, tackles the problem of categorizing a given review sentence into a set of pre-defined aspect categories. In recent years, deep learning approaches have brought revolutionary advances in multiple branches of natural language processing including sentiment analysis. In this paper, we propose a deep neural network method based on attention mechanism to identify different aspect categories of a given review sentence. Our model utilizes several attentions with different topic contexts, enabling it to attend to different parts of a review sentence based on different topics. Experimental results on two datasets in the restaurant domain released by SemEval workshop demonstrates that our approach outperforms existing methods on both datasets. Visualization of the topic attention weights shows the effectiveness of our model in identifying words related to different topics.