With advanced digitalisation, we can observe a massive increase of user-generated content
on the web that provides opinions of people on different subjects. Sentiment analysis is the …

A huge amount of data is generated daily leading to big data challenges. One of them is
related to text mining, especially text classification. To perform this task we usually need a …

Textual language is the most natural carrier of human emotion. In natural language
processing, textual emotion recognition (TER) has become an important topic due to its …

Human activity recognition (HAR) plays a vital role in many applications, such as
surveillance, in-home monitoring, and health care. Portable radar sensor has been …

Emotion detection and Sentiment analysis techniques are used to understand polarity or
emotions expressed by people in many cases, especially during interactive systems use …

Recently, leveraging pre-trained Transformer based language models in down stream, task
specific models has advanced state of the art results in natural language understanding …

Cross-domain sentiment classification uses knowledge from source domain tasks to
enhance the sentiment classification of the target task. It can reduce the workload of data …

In recent years, various studies have begun to use deep learning models to conduct
research in the field of human activity recognition (HAR). However, there has been a severe …

Text is a typical example of unstructured and heterogeneous data in which massive useful
knowledge is embedded. Sentiment analysis is used to analyze and predict sentiment …

Transfer learning usually utilizes the knowledge learned from the relative labeled source
domain to promote the model performance in the unlabeled or few labeled target domain …