Aspect Category Detection
8 papers with code • 4 benchmarks • 3 datasets
Aspect category detection (ACD) in sentiment analysis aims to identify the aspect categories mentioned in a sentence.
Cross-domain Aspect Category Transfer and Detection via Traceable Heterogeneous Graph Representation Learning
Aspect category detection is an essential task for sentiment analysis and opinion mining.
Leveraging Just a Few Keywords for Fine-Grained Aspect Detection Through Weakly Supervised Co-Training
In this work, we consider weakly supervised approaches for training aspect classifiers that only require the user to provide a small set of seed words (i. e., weakly positive indicators) for the aspects of interest.
Aspect category sentiment analysis (ACSA) aims to predict the sentiment polarities of the aspect categories discussed in sentences.
The developed models were evaluated using the collected dataset in terms of example-based and label-based metrics.
Joint Learning for Aspect and Polarity Classification in Persian Reviews Using Multi-Task Deep Learning
The purpose of this paper focuses on two sub-tasks related to aspect-based sentiment analysis, namely, aspect category detection (ACD) and aspect category polarity (ACP) in the Persian language.
Within the context of review analytics, aspects are the features of products and services at which customers target their opinions and sentiments.