New Challenges in Machine Learning and Natural Language Processing
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (20 July 2023) | Viewed by 1790
Special Issue Editor
Interests: natural language processing; text analytics; machine learning; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Natural Language Processing (NLP) has become a key technology of the information society. In recent years, research in NLP has mushroomed and many practical NLP applications have been brought to market including information retrieval systems and products for machine translation. Furthermore, recent large language models (LLM) such as GPT and BERT using Transformers have pushed the state-of-the-art on human-language interaction and large-scale document processing, However, it brings up numerous relevant unsolved theoretical and technological problems that await further research.
The Special Issue on new challenges in machine learning and NLP aims at assembling contributions by researchers from various fields of human language technology presenting results from the forefront of research and discussing the advanced state of the technology and its impact on our life.
Prof. Dr. John Atkinson Abutridy
Guest Editor
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Keywords
- computational phonology/morphology, word segmentation, and POS tagging
- syntax, semantics, grammar, and the lexicon
- lexical semantics and ontologies
- document summarization and abstracting
- natural language generation and neural models
- novel large language models
- paraphrasing and textual entailment
- parsing and chunking
- dialogue models
- speech processing
- industrial-strength applications of NLP
- novel machine learning methods and architectures for NLP
- novel deep learning architectures for NLP tasks
- spoken language analysis and generation, and speech-to-speech translation
- computational pragmatics
- human dialogue system and conversational agents
- computational models of discourse
- question answering
- word sense disambiguation
- information extraction and text mining
- semantic role labeling
- sentiment analysis and opinion mining
- machine translation and translation aids
- multilingual NLP
- machine learning for text mining
- corpus development and language resources
- evaluation methods and user studies
- explainable and interpretable NLP
- combining symbolic and neural approaches to NLP
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