Advancements and Challenges in NLP and Linguistic Text-Mining: Techniques, Applications, and Ethical Considerations
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: closed (15 February 2026) | Viewed by 1848
Special Issue Editors
Interests: NLP; text mining; algorithm theory; bin-packing; approximation algorithms
Interests: NLP; (temporal) formal concept analysis; fuzzy cognitive maps; semantic web; multi-agent systems; intelligent tutoring systems
Interests: semantic web; fuzzy logic; knowledge extraction; decision making; social media analytics
Special Issues, Collections and Topics in MDPI journals
Interests: rule-based NLP; lexicon-grammar; formal semantics; linguistic linked data; linguistic ontologies; knowledge automatic representation; artificial intelligence
Special Issue Information
Dear Colleagues,
Advances in Artificial Intelligence (AI) and deep learning (DL) are transforming how Natural Language Processing (NLP) and Information Retrieval (IR) tasks are performed. Techniques such as transformers and large-scale language models have revolutionized our ability to process, understand, and generate human language, while also exposing new vulnerabilities. NLP remains highly relevant, as it is one of the most accessible and popular methods of communicating with machines. IR has also garnered renewed interest, driven by new methods designed to support reasoning architectures.
This Special Issue explores a broad spectrum of topics, from fundamental techniques such as keyword extraction and topic modeling to advanced approaches involving linguistic text mining, deep learning, and neural networks.
Key areas of focus include information extraction, topic modeling, sentiment analysis, and the challenges associated with multilingual and cross-lingual processing, as well as Retrieval-Augmented Generation. This Special Issue also addresses ethical considerations such as bias, fairness, interpretability, and transparency in NLP systems. Contributions that investigate real-world applications in domains such as healthcare, law, and finance, where NLP and text mining are having a transformative impact, are particularly welcome.
By combining fundamental research with practical applications, this issue aims to offer a comprehensive overview of current challenges, emerging techniques, and future directions in the fields of NLP and IR.
The following is a list of the main topics covered by this Special Issue:
- Conversational AI and Dialogue Systems;
- Deep Learning and Transformer Models in NLP;
- Ethics, Bias, and Fairness in NLP;
- Information Extraction;
- Linguistic Text Mining;
- Multilingual and Cross-lingual NLP;
- Natural Language Understanding and Question Answering;
- NLP Applications in Specialized Domains;
- Pretrained Language Models and Transfer Learning;
- Text Classification and Sentiment Analysis;
- Text Mining in Information Retrieval;
- Topic Modeling and Document Clustering.
Dr. Alberto Postiglione
Dr. Francesco Orciuoli
Dr. Giuseppe Fenza
Dr. Mario Monteleone
Guest Editors
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Keywords
- natural language processing (NLP)
- linguistic text mining
- information extraction
- text classification
- sentiment analysis
- information retrieval
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