User-generated content on various Internet platforms is growing explosively, and contains
valuable information that helps decision-making. However, extracting this information …

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 …

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

Product reviews contain a large number of implicit aspects and implicit opinions. However,
most of the existing studies in aspect-based sentiment analysis ignored this problem. In this …

Aspect-based sentiment analysis (ABSA) has been extensively studied in recent years,
which typically involves four fundamental sentiment elements, including the aspect category …

Event extraction (EE) is a crucial research task for promptly apprehending event information
from massive textual data. With the rapid development of deep learning, EE based on deep …

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

Aspect-based sentiment analysis (ABSA) tasks aim to extract sentiment tuples from a
sentence. Recent generative methods such as Seq2Seq models have achieved good …

Aspect-based sentiment triplet extraction (ASTE) aims at recognizing the joint triplets from
texts, ie, aspect terms, opinion expressions, and correlated sentiment polarities. As a newly …

Multimodal named entity recognition (MNER) is a critical step in information extraction,
which aims to detect entity spans and classify them to corresponding entity types given a …