Prof. Rim Faiz
Department of Computer Science
IHEC, University of Carthage, Tunisia
Laboratory LARODEC
E-mail: Rim.Faiz@ihec.ucar.tn


Dr. Seifeddine Mechti
Department of Human Sciences
University of Sports and Physical Activities, Tunisia
ISSEPS, University of Sfax, Tunisia
Laboratory MIRACL and LARODEC
E-mail: Seif.mechtii@isseps.usf.tn

The exceptional growth of data sizes available on the Web, especially with the wide use of social networks has changed data processing. Then, traditional technologies are unable to handle this massive data. They presented often multidimensional constraints; Data come from different sources with diverse formats, should be treated in real time, and may be subject to different interpretations depending on the status of the end user. This is what has led to the emergence of Big Data.

This special issue is intended to provide an overview of the new research being carried out in the area of Big text mining searching focusing on emerging machine learning, deep learning methods and approaches for single and multiple language learning, understanding, generation and grounding, question answering and information retrieval, as well as applications of them to different domains like e-health and e-learning.

To this aim, the special session aims to gather researchers with broad expertise in various fields to discuss their cutting-edge work as well as perspectives on future directions in this exciting field. Original contributions are sought, covering the whole range of theoretical and practical aspects, technologies and systems in this research area.

BigTMSAI 2022 has the goal of a broad technical program. Relevant topics for the Session include, but are not limited to, the following areas (in alphabetical order):

• Big Data Management
• Big Text Mining and Information Extraction
• Big Data Analytics and Information Retrieval
• Artificial Intelligence
• Computational Social Science and Cultural Analytic
• Dialogue and Interactive Systems
• Discourse and Pragmatics
• Efficient Methods for NLP
• Ethics and NLP
• Generation
• Information Extraction
• Information Retrieval and Text Mining
• Interpretability and Analysis of Models for NLP
• Linguistic Theories, Cognitive Modeling and Psycholinguistics
• Machine Learning for NLP
• Machine Translation and Multilinguality
• NLP Applications
• Phonology, Morphology and Word Segmentation
• Question Answering
• Resources and Evaluation
• Semantics: Lexical, Sentence level, Textual Inference and Other areas
• Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Speech, Vision, Robotics, Multimodal Grounding
• Summarization