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Machine Learning and Knowledge Extraction (MAKE) (ISSN 2504-4990) is an inter-disciplinary, cross-domain, peer-reviewed, scholarly open access journal to provide a platform to support the international machine learning community.
1. Data: data ecosystems, data-preprocessing, data integration, data fusion, data mapping, data generation, and knowledge representation
2. Learning: automatic and interactive machine learning methodologies, methods, algorithms and tools, comparisons to human cognition
3. Visualization: Data visualization, visual analysis, comparisons to human perception, human-computer interaction
4. Privacy: data protection, safety and security, interpretability, transparency, causality, usability, acceptance, ethical, legal and social issues
5. Network: Graph-based machine learning, graph data mining, language graphs, probabilistic graphical models
6. Topology: Topological data analysis, computational topology, homology, homotopy, persistence, manifolds, simplical complexes
7. Entropy: Entropy-based data mining, longitudinal and time dependent data analysis and knowledge discovery
Company Details
- Employees
- 1
- Industry
- Book And Periodical Publishing
- Keywords
- Amsterdam.
Make Mdpi Questions
MAKE MDPI's website is https://www.mdpi.com/journal/make
MAKE MDPI's LinkedIn profile is https://www.linkedin.com/company/make-mdpi
MAKE MDPI has
1 employees.
View email and phone details for 1
employees at MAKE MDPI.
MAKE MDPI's industry is
Book and Periodical Publishing
MAKE MDPI's top competitors are
Elsevier,
Solids Mdpi,
Quantum Neural Technologies (Qn⊗t) Sa,
Informatics Mdpi,
Mdpi,
Entropy Mdpi,
Iot Mdpi,
Big Data And Cognitive Computing Mdpi,
Jfmk Mdpi,
Kleio Capital Management Llc.
MAKE MDPI's categories are Book and Periodical Publishing
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Lorenzo Carnevale
Assistant Professor At University Of Messina
Messina, Sicily, Italy, Italy
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