- 6.0Impact Factor
- 9.9CiteScore
- 26 daysTime to First Decision
Selected Papers from CD-MAKE 2021 and ARES 2021
Special Issue Information
Dear Colleagues,
This Special Issue will mainly consist of extended papers selected from papers presented at the 5th International Cross Domain Conference for Machine Learning & Knowledge Extraction (CD-MAKE 2021) as well as the 16th International Conference on Availability, Reliability and Security (ARES 2021). Please visit the conference websites for a detailed description: https://www.ares-conference.eu/ and https://cd-make.net/
Prof. Dr. Simon Tjoa
Prof. Dr. Edgar Weippl
Prof. Dr. Andreas Holzinger
Peter Kieseberg
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. Machine Learning and Knowledge Extraction is an international peer-reviewed open access quarterly 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 1800 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
- DATA – data fusion, preprocessing, mapping, knowledge representation, environments, etc.
- LEARNING – algorithms, contextual adaptation, causal reasoning, transfer learning, etc.
- VISUALIZATION – intelligent interfaces, human-AI interaction, dialogue systems, explanation interfaces, etc.
- PRIVACY – data protection, safety, security, reliability, verifiability, trust, ethics and social issues, etc.
- NETWORK – graphical models, graph-based machine learning, Bayesian inference, etc.
- TOPOLOGY – geometrical machine learning, topological and manifold learning, etc. ENTROPY – time and machine learning, entropy-based learning, etc.
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Published Papers
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