Applications, Challenges and Future Direction of Natural Language Processing Based on Deep Learning
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 10 March 2025 | Viewed by 12283
Special Issue Editor
Special Issue Information
Dear Colleagues,
The field of natural language processing (NLP) has seen significant advancements in recent years with the integration of deep learning techniques. NLP is a crucial area of Artificial Intelligence that enables machines to process, understand, and generate human languages. Applications of NLP include corpus analysis, information retrieval, machine translation, semantic analysis, text categorization, and many others. With the rise in these approaches, NLP plays a critical role in solving daily problems and sharing human workload. The development of NLP directly affects the progress of information technology and the quality of human–computer interactions.
This Special Issue aims to gather researchers from various fields and backgrounds who use NLP methods to solve diverse problems. It provides an opportunity to report on the latest works and achievements and introduce new perspectives to the future directions of the NLP field. We welcome original research articles reporting the development of NLP novel models and algorithms, as well as NLP application papers with novel ideas, especially based on deep learning.
We encourage submissions dealing with text classification, sentiment analysis, authorship attribution, text document clustering, detection of fake news, machine translation, text summarization, development of chatbots, grammar checking, and interdisciplinary NLP studies. However, we do not limit the examples to these and welcome other innovative NLP applications. Contributions can focus on processing approaches, algorithms, and methods, and we welcome survey papers and reviews.
We invite researchers, practitioners, and experts in the field of NLP to submit their latest work and contribute to this exciting Special Issue. All submissions will undergo a rigorous peer-review process to ensure the quality and relevance of the content.
We look forward to receiving your contributions and to shaping the future of NLP together.
- Natural language understanding and generation
- Machine translation
- Question answering and dialogue systems
- Knowledge extraction and modelling
- Knowledge-graph-based approaches
- Text summarization and style transfer
- Text classification, topic extraction, and discourse analysis
- Fake news, misinformation, and disinformation detection
- Echo chamber and polarization detection
- Sentiment analysis, emotion recognition, and stance detection
- Document analysis, information extraction, and text mining
- Behavior modeling
- Social and psychological applications of NLP
- Multilanguage approaches
- Transfer learning in NLP
Dr. Bo Wang
Guest Editor
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