Can I read A Unified One-Step Solution for Aspect Sentiment Quad Prediction on EtoBox?

A Unified One-Step Solution for Aspect Sentiment Quad Prediction by Zhou, Junxian; Yang, Haiqin; He, Yuxuan; Mou, Hao; Yang, Junbo is a scholarly article available to read on EtoBox.

What is A Unified One-Step Solution for Aspect Sentiment Quad Prediction about?

Aspect sentiment quad prediction (ASQP) is a challenging yet significant subtask in aspect-based sentiment analysis as it provides a complete aspect-level sentiment structure. However, existing ASQP datasets are usually small and low-density, hindering technical advancement. To expand the capacity, in this paper, we release two new datasets for ASQP, which contain the following characteristics: larger size, more words per sample, and higher density. With such datasets, we unveil the shortcomings of existing strong ASQP baselines and therefore propose a unified one-step solution for ASQP, namely One-ASQP, to detect the aspect categories and to identify the aspect-opinion-sentiment (AOS) triplets simultaneously. Our One-ASQP holds several unique advantages: (1) by separating ASQP into two subtasks and solving them independently and simultaneously, we can avoid error propagation in pipeline-based methods and overcome slow training and inference in generation-based methods; (2) by introducing sentiment-specific horns tagging schema in a token-pair-based two-dimensional matrix, we can exploit deeper interactions between sentiment elements and efficiently decode the AOS triplets; (3) we

Author

Zhou, Junxian; Yang, Haiqin; He, Yuxuan; Mou, Hao; Yang, Junbo

Published

2023

Language

EN