Advances in Data Mining for Complex Systems
A special issue of Information (ISSN 2078-2489).
Deadline for manuscript submissions: 31 May 2026 | Viewed by 11
Special Issue Editors
Interests: natural language understanding; NLP; artificial intelligence
Interests: text analysis; NLP; deep learning; optimization; applications of deep learning in cyber security; integrating security and NLP
Special Issues, Collections and Topics in MDPI journals
Interests: computer architecture; machine learning; image and digital signal processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are pleased to invite you to submit your original contributions to the Special Issue of Information, titled “Advances in Data Mining for Complex Systems”. Advanced data mining approaches for natural language processing (NLP) are required due to the expanding volume of multilingual data and the complexity of digital communication. Recent advances in deep learning and multilingual models have improved text analysis, but there are still major challenges in identifying offensive language, ensuring factual consistency, and enabling effective cross-lingual classification.
The advancement of data mining techniques for text analysis is the main emphasis of our special issue, especially in fields where current methods suffer from biases, inconsistencies, and cross-lingual constraints. Since false information and untrustworthy sources continue to erode confidence in automated systems, factual consistency is one of the main issues.
Cross-lingual text categorization presents an additional difficulty, as models developed for high-resource languages sometimes do not apply well to low-resource or morphologically complicated languages. This problem is especially pertinent in multilingual domains, where multilingual representation learning and domain adaptation can be very important. We also encourage studies on more general developments in NLP for complex systems, such as hybrid models, combining deep learning with knowledge graphs, and other innovative architectures. Other important areas of focus are ethical issues, such as prejudice reduction and fairness in NLP.
Prof. Dr. Lei Li
Dr. Natalia Vanetik
Dr. Shlomo Greenberg
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. Information 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 1600 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.
Keywords
- text classification
- factual consistency
- multilingual analysis
- natural language understanding
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