Recently, sequential transfer learning emerged as a modern technique for applying the
“pretrain then fine-tune” paradigm to leverage existing knowledge to improve the …

Humans are increasingly integrated with devices that enable the collection of vast
unstructured opinionated data. Accurately analysing subjective information from this data is …

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 …

The rise of sophisticated black-box machine learning models in Artificial Intelligence
systems has prompted the need for explanation methods that reveal how these models work …

To provide explainable and accurate aspect terms and the corresponding aspect–sentiment
detection, it is often useful to take external domain-specific knowledge into consideration. In …

Aspect-based sentiment analysis (ABSA) aims at determining the sentiment polarity of the
given aspect term in a sentence. Recently, graph convolution network (GCN) has been used …

Aspect-based sentiment analysis (ABSA) is a fine-grained task that detects the sentiment
polarities of particular aspect words in a sentence. With the rise of graph convolution …

The increasing interest around emotions in online texts creates the demand for financial
sentiment analysis. Previous studies mainly focus on coarse-grained document-/sentence …

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

Aspect-based sentiment analysis (ABSA) aims to analyze the sentiment polarity of a given
text towards several specific aspects. For implementing the ABSA, one way is to convert the …