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Overview
Data Mining and Knowledge Discovery is a leading technical journal focusing on the extraction of information from vast databases.
- Publishes original research papers and practice in data mining and knowledge discovery.
- Provides surveys and tutorials of important areas and techniques.
- Offers detailed descriptions of significant applications.
- Addresses theory, foundational issues, data mining methods, and knowledge discovery processes.
- Renowned for its focus on techniques and applications.
This is a transformative journal, you may have access to funding.
- Main Editor
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- Eyke Hüllermeier
- Journal Impact Factor
- 2.8 (2023)
- 5-year Journal Impact Factor
- 5.3 (2023)
- Submission to first decision (median)
- 21 days
- Downloads
- 453,666 (2023)
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Latest articles
Journal updates
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Call for Papers: Special Issue on Explainable and Interpretable Machine Learning and Data Mining
Guest Editors: Martin Atzmueller, Johannes Fuernkranz, Tomas Klieger, Ute Schmid
Submission Deadline: extended to June 15th, 2021 -
Call for Papers: Special issue on Bias and Fairness in AI
Guest Editors: T. Calders, E. Ntoutsi, M. Pechenizkiy, B. Rosenhahn, S. Ruggieri
Submission deadline: August 31, 2021 -
Call for Papers: ECMLPKDD 2022
Submission deadline: 11 February, 2022
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Call for Papers: Special Issue on Programming Language Processing
Submission Deadline: November 30, 2021
Guest Editors: Chang Xu, Siqi Ma, David Lo
Journal information
- Electronic ISSN
- 1573-756X
- Print ISSN
- 1384-5810
- Abstracted and indexed in
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- ACM Digital Library
- ANVUR
- BFI List
- Baidu
- CLOCKSS
- CNKI
- CNPIEC
- Current Contents/Engineering, Computing and Technology
- Current Index to Statistics
- DBLP
- Dimensions
- EBSCO
- EI Compendex
- Google Scholar
- INSPEC
- Japanese Science and Technology Agency (JST)
- Mathematical Reviews
- Naver
- OCLC WorldCat Discovery Service
- Portico
- ProQuest
- SCImago
- SCOPUS
- Science Citation Index Expanded (SCIE)
- TD Net Discovery Service
- UGC-CARE List (India)
- Wanfang
- zbMATH
- Copyright information
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