Sentiment analysis (SA) aims to understand the attitudes and views of opinion holders with
computers. Previous studies have achieved significant breakthroughs and extensive …

Information extraction suffers from its varying targets, heterogeneous structures, and
demand-specific schemas. In this paper, we propose a unified text-to-structure generation …

As an important fine-grained sentiment analysis problem, aspect-based sentiment analysis
(ABSA), aiming to analyze and understand people's opinions at the aspect level, has been …

In contrast to earlier ABSA studies primarily concentrating on individual sentiment
components, recent research has ventured into more complex ABSA tasks encompassing …

The challenge of information extraction (IE) lies in the diversity of label schemas and the
heterogeneity of structures. Traditional methods require task-specific model design and rely …

Aspect-based sentiment analysis (ABSA) has received increasing attention recently. ABSA
can be divided into multiple tasks according to the different extracted elements. Existing …

The rapid development of aspect-based sentiment analysis (ABSA) within recent decades
shows great potential for real-world society. The current ABSA works, however, are mostly …

Aspect-based sentiment analysis (ABSA) is an emerging fine-grained sentiment analysis
task that aims to extract aspects, classify corresponding sentiment polarities and find …

Pragmatics, situated in the domains of linguistics and computational linguistics, explores the
influence of context on language interpretation, extending beyond the literal meaning of …

Sentiment analysis is an important tool to automatically understand the user-generated
content on the Web. The most fine-grained sentiment analysis is concerned with the …