Deep Learning Brasil at ABSAPT 2022: Portuguese Transformer Ensemble Approaches
원문 초록
Aspect-based Sentiment Analysis (ABSA) is a task whose objective is to classify the individual sentiment polarity of all entities, called aspects, in a sentence. The task is composed of two subtasks: Aspect Term Extraction (ATE), identify all aspect terms in a sentence; and Sentiment Orientation Extraction (SOE), given a sentence and its aspect terms, the task is to determine the sentiment polarity of each aspect term (positive, negative or neutral). This article presents we present our participation in Aspect-Based Sentiment Analysis in Portuguese (ABSAPT) 2022 at IberLEF 2022. We submitted the best performing systems, achieving new state-of-the-art results on both subtasks.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
UnifiedABSA: A Unified ABSA Framework Based on Multi-task Instruction Tuning
MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction
InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis
A Deep Convolutional Neural Networks Based Multi-Task Ensemble Model for Aspect and Polarity Classification in Persian Reviews
Jointly Modeling Aspect and Polarity for Aspect-based Sentiment Analysis in Persian Reviews
A Unified Generative Framework for Aspect-Based Sentiment Analysis
토론
이 논문과 연결된 포럼 글이 아직 없습니다.