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Special Session 2:
Machine Learning for Natural Language Processing

Nowadays, with billions of text documents overflowing from the web, there is a great need for efficient techniques that process and analyze large amounts of data. Modern NLP techniques makes it possible for computers to read and interpret text, hear and understand speech, measure sentiment, and determine which parts in a document are important. In this context, machine learning (ML) has become an essential tool for natural language processing, and has emerged in different NLP application scenarios, such as sentiment analysis, document classification, text summarization, speech recognition, etc. Despite the success of ML algorithms in this application, several existing methods are challenged by the input data, which are noisy, heterogeneous, sparse and high dimensional. From this point of view, recent ML techniques, such as those based on deep learning, reinforcement learning, few-shot learning and so on, have shown an improvement in recent years in solving challenging NLP problems.

Scope:

After the success of the previous sessions of ML for NLP (2020, 2021, 2022, 2024), the fifth edition of this special session aims to highlight recent progress in NLP techniques and methodologies, with a focus on the latest advances in machine learning applications for natural language processing. The purpose of this session is to bring together professionals, researchers and experts in natural language processing and machine learning in order to discuss the main challenges and define possible future directions in this area.

Topics:

This session invites submissions with high-quality works that are related – but are not limited to – the topics below:

• Deep learning for NLP
• Reinforcement Learning for NLP
• Unsupervised Learning for NLP
• Automatic machine translation
• Automatic document summarization
• Text classification
• Text detection and recognition from images
• Question Answering systems
• Transfer Learning for NLP
• Active Learning for NLP
• Speaker identification
• Speech recognition
• Speech to Text
• Text generation
• Sentiment analysis
• Real-life and industrially relevant NLP applications
• Email filtering
• Chatbot
• News generation
• Meeting analysis
• Fact Checking
• CVs analysis and classification

Chairs: Rim Hantach, ENGIE, France; Vasile Palade, Coventry University, UK

Bio: Rim Hantach is a research scientist at ENGIE France. She is working on deep learning, computer vision, NLP, knowledge graph, and graph representation learning for text and image analysis. She organized different workshops related to text document analysis, such as the 1st edition of the GLESDO workshop, Machine Learning for NLP, Deep learning meets Ontology and NLP, Deep learning for Ontology, etc.
Vasile Palade is Professor of Artificial Intelligence and Data Science in the Centre for Computational Science and Mathematical Modelling at Coventry University, UK. His research interests are in the area of machine learning/computational intelligence. Vasile Palade is author and co-author of more than 250 papers in journals and conference proceedings as well as books on machine learning and applications. He has also co-edited several books including conference proceedings.

Technical Committee

• Abdulrahman Alatahhan, Leeds Becket University, UK
• Daniel Neagu, University of Bradford, UK
• Xiaorui Jiang, Coventry University, UK
• Rafika Boutalbi, University of Stuttgart, Germany
• Lazhar Labiod, University of Paris Descartes, France
• Sanju Tiwari, Universidad Autonoma de Tamaulipas, Mexico
• Amir Laadhar, Aalborg University, Denmark
• Linda Elmhadhbi, University of Toulouse, France

Paper Submission Instructions

All papers will be double-blind reviewed and must present original work.

• CMT Submission Site
• Select the track: Special Session 2: Machine Learning for Natural Language Processing

Papers submitted for reviewing should conform to IEEE specifications. Manuscript templates can be downloaded from:

• IEEE website

Keydates

• Submission due date: September 9, 2024
• Notification of Acceptance: September 25, 2024
• Camera Ready Papers: October 5, 2024
• Pre-registration: October 15, 2024
• Conference: December 18-20, 2024

Registration

In order for your paper to be presented in the virtual session and published in the proceedings you must register to the conference.

Paper Presentation Instructions

The papers submitted to this track will be presented in person as part of the conference. There is no virtual presentation for this session.