Aspect-Category-Opinion-Sentiment Quadruple Extraction
4 papers with code • 2 benchmarks • 3 datasets
Aspect-Category-Opinion-Sentiment (ACOS) Quadruple Extraction is the task with the goal to extract all aspect-category-opinion-sentiment quadruples in a review sentence. ( and provide full support for aspect-level sentiment analysis with implicit aspects and opinions if possible )
Most implemented papers
Aspect-Category-Opinion-Sentiment Quadruple Extraction with Implicit Aspects and Opinions
In this work, we introduce a new task, named Aspect-Category-Opinion-Sentiment (ACOS) Quadruple Extraction, with the goal to extract all aspect-category-opinion-sentiment quadruples in a review sentence and provide full support for aspect-based sentiment analysis with implicit aspects and opinions.
Aspect-Category-Opinion-Sentiment Extraction Using Generative Transformer Model
This paper proposes a method of using BART-Aspect-Based-Sentiment-Analysis (BARTABSA), a sentiment analysis model that aims to unify the previous Aspect Based Sentiment Analysis subtask - namely Aspect-Opinion pair extraction and Aspect-Opinion-Sentiment triplet extraction, and solve them without changing the core algorithm or adding other models to it - to solve the ACOS subtask.
MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction
Generative methods greatly promote aspect-based sentiment analysis via generating a sequence of sentiment elements in a specified format.
E2TP: Element to Tuple Prompting Improves Aspect Sentiment Tuple Prediction
Generative approaches have significantly influenced Aspect-Based Sentiment Analysis (ABSA), garnering considerable attention.