Attention is an increasingly popular mechanism used in a wide range of neural
architectures. The mechanism itself has been realized in a variety of formats. However …

Deep learning has emerged as a powerful machine learning technique that learns multiple
layers of representations or features of the data and produces state‐of‐the‐art prediction …

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 …

Attention is an important mechanism that can be employed for a variety of deep learning
models across many different domains and tasks. This survey provides an overview of the …

Disentangled Representation Learning (DRL) aims to learn a model capable of identifying
and disentangling the underlying factors hidden in the observable data in representation …

Aspect based sentiment analysis (ABSA) involves three fundamental subtasks: aspect term
extraction, opinion term extraction, and aspect-level sentiment classification. Early works …

Target-based sentiment analysis or aspect-based sentiment analysis (ABSA) refers to
addressing various sentiment analysis tasks at a fine-grained level, which includes but is not …

Aspect sentiment triplet extraction (ASTE), which aims to identify aspects from review
sentences along with their corresponding opinion expressions and sentiments, is an …

The domain of Aspect-based Sentiment Analysis, in which aspects are extracted, their
sentiments are analysed and sentiments are evolved over time, is getting much attention …

One key task of fine-grained sentiment analysis of product reviews is to extract product
aspects or features that users have expressed opinions on. This paper focuses on …