Ranking & Metrics
Rank:
#2536H Index:
22SJR:
1,351Ref Doc:
56,95Quartile:
Q1Coverage:
2020-2022Total Refs:
6322Journal Information
Machine Learning: Science and Technology
26322153
Institute of Physics Publishing
Artificial Intelligence
Human-Computer Interaction
United Kingdom
Western Europe
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Aims & Scope of the Journal
Machine Learning: Science and Technology is a research journal that publishes research related to Human-Computer Interaction. This journal is published by the Institute of Physics Publishing. The ISSN of this journal is 26322153. Based on the Scopus data, the SCImago Journal Rank (SJR) of Machine Learning: Science and Technology is 1,351.
Also, check the other important details below like Publisher, ISSN, Ranking, Indexing, Impact Factor (if applicable), Publication fee (APC), Review Time, and Acceptance Rate of Machine Learning: Science and Technology.
According to Clarivate's JCR, the journals indexed in SCIE/SSCI have an impact factor.
How to publish in Machine Learning: Science and Technology
This journal covers the fields/ categories related to Human-Computer Interaction. If your research field is related to Human-Computer Interaction, then visit the official website of Machine Learning: Science and Technology and send your manuscript.
Tips for publishing in Machine Learning: Science and Technology:
- - Selection of research problem.
- - Presenting a solution.
- - Designing the paper.
- - Make your manuscript publication worthy.
- - Write an effective results section.
- - Mind your references.
Acceptance Rate
Acceptance rate is the ratio of the number of articles submitted to the number of articles published. Researchers can check the acceptance rate on the journal website. Even you can Contact the editor of the journal.
Journal Publication Time
Journals usually ask reviewers to provide their reviews within 3-4 weeks. However, few journals have a mechanism to enforce the deadline, which is why it can be hard to predict how long the peer review process will take.
The review time also depends upon the quality of a research paper.