Text classification is a process of classifying documents into predefined categories through
different classifiers learned from labelled or unlabelled training samples. Many researchers …

Social media platforms have become a common place for information exchange among their
users. People leave traces of their emotions via text expressions. A systematic collection …

The use of neural machine algorithms for English translation is a hot topic in the current
research. English translation using the traditional sequential neural framework, which is too …

Language model (LM) has become a common method of transfer learning in Natural
Language Processing (NLP) tasks when working with small labeled datasets. An LM is …

Textual data have been a major form to convey internet users' content. How to effectively
and efficiently discover latent topics among them has essential theoretical and practical …

Existing topic modeling and text segmentation methodologies generally require large
datasets for training, limiting their capabilities when only small collections of text are …

Topic modeling discovers the hidden topics in a document collection. Most of the existing
topic models focus only on word usage and generate the topics based on the word …

With the rapid development of web services, social media has been a prevalent and readily
way for people to express themselves and share their daily lives. Consequently, numerous …

In the current information era over the internet, social media has become one of the
essential information sources for users. While the text is the primary information …

Topic models extract commonly occurring latent topics from textual data. Statistical models
such as Latent Dirichlet Allocation do not produce dense topic embeddings readily …