Machine Learning Applications in Natural Language Processing

Dear Colleagues,

Currently, natural language processing (NLP) is one of the most important technologies. In the era of big data, especially with the increasing amount of text available online, the progress of NLP has grown rapidly. In NLP, large-scale datasets (e.g., text corpora and multilingual databases) enable the training of advanced models.

Machine learning is a branch of artificial intelligence that focuses on developing algorithms to learn from data and improve their performance over time. With their development, they have revolutionized NLP, enabling tasks such as language translation, large-scale text processing, document summarization, human-like response generation, and speech recognition to be conducted with greater accuracy and efficiency. Furthermore, interdisciplinary research on machine learning-based NLP has been expanded to healthcare, finance, education, entertainment, etc.

The combination of machine learning and NLP has led to significant advancements in the field, opening up new possibilities for applications.

This Special Issue aims to provide a comprehensive platform to explore the latest advancements in machine learning applications in NLP, with a specific emphasis on the integration of big data, deep learning, and large language model technologies. In essence, this Special Issue’s themes are a subset of "Big Data and Cognitive Computing", focusing specifically on NLP-driven advancements that leverage data-intensive, AI-powered methods to enhance machine intelligence. By showcasing research and innovative approaches in the design, development, and implementation of machine learning applications in NLP, this Special Issue contributes directly to the evolution of cognitive computing systems that aim to mimic human cognitive abilities. Cognitive computing relies on big data to simulate human-like reasoning, decision-making, and language understanding.

This Special Issue also places high value on interdisciplinary research that explores the practical applications of NLP in various domains.

Original research articles and reviews are welcome in this Special Issue. The scope includes, but is not limited to, the following topics:

• Text classification and clustering;
• Text mining;
• Text summarization;
• Information extraction;
• Information retrieval;
• Machine translation;
• Question answering;
• Sentiment analysis;
• Large language models;
• Multimodal NLP;
• NLP applications in healthcare;
• NLP applications in finance;
• NLP applications in education;
• NLP applications in entertainment;
• Explainable artificial intelligence for NLP;
• Semiotic-aware NLP;
• Semiotics for NLP explainability.

We look forward to receiving your contributions.

Dr. Ying Weng
Prof. Dr. Kecheng Liu
Dr. Chao Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Big Data and Cognitive Computing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• big data
• deep learning
• large language model
• multimodal
• XAI