Symmetry in Machine Learning and Text Mining
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 31 July 2026 | Viewed by 268
Special Issue Editor
Special Issue Information
Dear Colleagues,
Machine learning and text mining continue to advance rapidly, driven by new models, large-scale data, and expanding application domains. Since the early stages of learning theory, symmetry has played an important role in understanding patterns, reducing complexity, and guiding model design. Concepts such as invariance, equivariance, structural balance, and geometric regularity appear naturally in many real-world datasets. With the growing influence of deep learning, symmetry has not lost its relevance. Instead, its importance has increased, as modern architectures rely more and more on structured representations, stable behaviors, and efficient learning mechanisms.
In this Special Issue, we aim to highlight academic advances and practical applications that show how symmetry contributes to progress in machine learning and text mining. Topics include symmetry-aware neural architectures, geometric and group-theoretic learning, symmetric pattern discovery, improved text representations, robustness through invariance, and symmetry-driven improvements in classification, clustering, and sequence modeling.
We warmly welcome original research articles and comprehensive reviews that deepen our understanding of symmetry and its role in next-generation intelligent systems.
Prof. Dr. Abdelkrim El Mouatasim
Guest Editor
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 250 words) can be sent to the Editorial Office for assessment.
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. Symmetry 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 2400 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
- symmetry
- machine learning
- text mining
- invariance
- equivariance
- geometric deep learning
- representation learning
- natural language processing
- pattern analysis
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