This survey focuses on deep learning-based aspect-level sentiment classification (ASC),
which aims to decide the sentiment polarity for an aspect mentioned within the document …

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 …

Continual learning (CL) learns a sequence of tasks incrementally with the goal of achieving
two main objectives: overcoming catastrophic forgetting (CF) and encouraging knowledge …

Due to advancements in data collection, storage, and processing techniques, machine
learning has become a thriving and dominant paradigm. However, one of its main …

Sentiment analysis is the computational study of people's opinions, sentiments, emotions,
moods, and attitudes. This fascinating problem offers numerous research challenges, but …

This paper studies continual learning (CL) of a sequence of aspect sentiment classification
(ASC) tasks. Although some CL techniques have been proposed for document sentiment …

This paper studies continual learning (CL) of a sequence of aspect sentiment classification
(ASC) tasks in a particular CL setting called domain incremental learning (DIL). Each task is …

This paper focuses on learning domain-oriented language models driven by end tasks,
which aims to combine the worlds of both general-purpose language models (such as ELMo …

Sentiment analysis through the investigation on commodity reviews will be of great
importance to commodity quality improvement of the seller and subsequent consumption …

Human beings acquire knowledge by a continually learning process. They learn through
experience, accumulate knowledge, and employ it to perform the task at hand. The main aim …