Data Mining and Knowledge Discovery
Q1 Journal
Journal
Country
Netherlands
Western Europe
Subject Area and Category
Computer Science
└
Computer Networks and Communications
Q1
└
Computer Science Applications
Q1
└
Information Systems
Q1
Publisher
SJR 2025
1.200
Q1
SJR Score
H-Index
131
Citations / Doc (2yr)
6.52
Total Docs. (latest)
89
Total Citations (3yr)
1,740
Publication type
Journals
ISSN
13845810, 1573756X
Coverage
1997-2026
Journal Rank
#3,630
Subject Categories
Computer Networks and Communications
Q1
Computer Science Applications
Q1
Information Systems
Q1
Subject Areas
Aims & Scope
Advances in data gathering, storage, and distribution have created a need for computational tools and techniques to aid in data analysis.
Data Mining and Knowledge Discovery in Databases (KDD) is a rapidly growing area of research and application that builds on techniques and theories from many fields, including statistics, databases, pattern recognition and learning, data visualization, uncertainty modelling, data warehousing and OLAP, optimization, and high performance computing.
Abstracting & Indexing
Scopus
Google Scholar
Web of Science
Detailed Metrics
| Total Docs. (latest) | 89 |
| Total Docs. (3 years) | 268 |
| Total Refs. | 4,772 |
| Total Citations (3 years) | 1,740 |
| Citable Docs. (3 years) | 267 |
| Citations / Doc. (2 years) | 6.52 |
| Ref. / Doc. | 53.62 |
| % Female | 23.7% |
Metrics Visualization
Latest year data vs 3-year cumulative figures
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