New Techniques of Machine Learning and Deep Learning in Text Classification

Dear Colleagues,

Text classification is at the heart of a variety of software systems that process text data at a large scale. It performs fundamental tasks in natural language processing and is applied broadly for sentiment analysis, spam detection, and topic labeling. Nowadays, data can be easily collected from various sources with diverse formats, with text being one of the most common types of unstructured data. However, as  data size grows exponentially, traditional technologies have become unable to handle such massive and unstructured data, leading to the emergence of big data in text classification and cutting-edge machine learning and deep learning techniques that can perform high-accuracy lower-level engineering and computation functions.

This Special Issue aims to bring together cutting-edge research from both academia and the industry focusing on new techniques for machine learning and deep learning for text classification. To this aim, we are calling for researchers with broad expertise in various fields to present their cutting-edge work as well as perspectives on future directions in this exciting field. Submissions covering all theoretical and practical aspects, technologies, and systems in this research area are welcome.

Dr. Duy-Tai Dinh
Dr. Uday Kiran RAGE
Guest Editors

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