Machine Learning and Knowledge Extraction
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| Discipline | Machine learning, artificial intelligence, data science |
|---|---|
| Language | English |
| Edited by | Andreas Holzinger |
| Publication details | |
| History | 2019–present |
| Publisher | MDPI (Switzerland) |
| Frequency | Quarterly |
| Yes | |
| License | Creative Commons Attribution License |
| 6.0 (2023) | |
| Standard abbreviations | |
| ISO 4 | Mach. Learn. Knowl. Extr. |
| Indexing | |
| ISSN | 2504-4990 |
| Links | |
Machine Learning and Knowledge Extraction (MAKE) is a peer-reviewed open-access scientific journal covering research on machine learning, knowledge extraction and related areas of data-driven artificial intelligence. It is published by MDPI and was launched in 2019 with Andreas Holzinger as founding Editor-in-Chief.
The journal publishes research articles, reviews, tutorials and short notes spanning topics such as data ecosystems, interactive and automated machine learning, explainable AI, privacy, graph learning and topological data analysis
Abstracting and indexing
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According to the Journal Citation Reports, the journal has a 2024 impact factor of 6.0.[5]
References
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