Machine Learning and Data Analysis: Bridging Theory and Real-World Solutions
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 15 July 2025 | Viewed by 467
Special Issue Editors
Interests: data science; machine learning; natural language processing; language technologies; machine translation; business analytics; open data
Interests: machine learning; data science; machine translation; natural language processing; language technologies; information systems; databases
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; machine learning; interpretable machine learning; educational data mining; natural language processing; machine translation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The MDPI journal Applied Sciences invites submissions to a Special Issue on “Machine Learning and Data Analysis: Bridging Theory and Real-World Solutions”.
The goal of this Special Issue is to investigate how machine learning and data analysis can be utilized for solving real-world problems in a variety of domains. It presents research that transforms theoretical breakthroughs into practical applications. A wide range of subjects are covered in this issue, including the creation of machine learning algorithms and innovative methods for analyzing data, as well as their use in various fields.
In this Special Issue, original and unpublished works with results in any way related to machine learning, data science, natural language processing, and linked areas are welcome. We welcome various types of experimental and methodological aspects on novel solutions in machine learning and data analysis, including the following:
- Research, analysis, or implementation approaches and innovations in machine learning and data analysis methods;
- User studies on the application of machine learning and data science in various fields;
- Emerging technologies and evaluation of integrative solutions for data analysis and predictive analytics;
- Corpora and other digital resources that are essential to data science;
- Research on natural language processing and language and speech technologies;
- Strategies, challenges, and opportunities in data science. Nevertheless, submissions with a strong theoretical contribution are also desirable.
Topics of interest include, but are not limited to, the following:
- Innovations in machine learning and data analysis;
- Analysis of machine learning methods and approaches;
- Emerging technologies and evaluation of deep learning;
- Integrative approaches to machine learning and data analysis;
- Advanced data analysis and predictive data analytics;
- Open data analytics and innovations;
- Image recognition and generation;
- Digital corpora and other resources for data science;
- Research on natural language processing;
- Innovative language technologies;
- Novel approaches to speech technologies;
- Real-world data-driven solutions and new strategies;
- Data-driven decision making;
- Challenges and opportunities in data science;
- Ethical considerations and legal issues in artificial intelligence;
- Application of machine learning and data science in various fields.
Prof. Dr. Sanja Seljan
Dr. Ivan Dunđer
Prof. Dr. Marija Brkić Bakarić
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. Applied Sciences is an international peer-reviewed open access semimonthly 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
- machine learning
- deep learning
- data analysis
- data science
- data mining
- natural language procssing
- language technologies
- speech technologies
- open data
- image recognition
- predictive analytics
- digital resources
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