Data Mining and Knowledge Discovery

88.3k citations
1.2k papers · · active since 1997

Impact in

    • Time Series Analysis and Forecasting
    • Advanced Clustering Algorithms Research
    • Anomaly Detection Techniques and Applications
    • Machine Learning and Data Classification

Papers in

Data Mining and Knowledge Discovery

1.1k papers receiving 83.5k citations

Peers

Data Mining and Knowledge Discovery
Comparison fields: 5 of 235
  • Signal Processing 9.7k
  • Artificial Intelligence 28.1k
  • Information Systems 18.9k
  • Computational Mathematics 315
  • Computer Vision and Pattern Recognition 7.8k
Replace ACM Transactions on Intelligent Systems and Technology with:
ACM Transactions on Intelligent Systems and Technology China
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) United States
Journal of Machine Learning Research United States
The VLDB Journal United States
ACM Transactions on Information Systems China
IEEE Communications Surveys & Tutorials United States
ACM Transactions on Knowledge Discovery from Data China
IEEE Transactions on Evolutionary Computation China
IEEE Signal Processing Magazine United States
Journal of Artificial Intelligence Research United States
Data Mining and Knowledge Discovery relative to ACM Transactions on Intelligent Systems and Technology China ACM Transactions on Intelligent Systems and Technology's profile →
Citations per field
00.5×2×2.6×
ACM Transactions on Intelligent Systems and Technology · 1×
Citations per year

Countries where authors publish in Data Mining and Knowledge Discovery

Since Specialization
Citations

This map shows the geographic impact of research published in Data Mining and Knowledge Discovery. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Data Mining and Knowledge Discovery with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Data Mining and Knowledge Discovery more than expected).

Fields of papers published in Data Mining and Knowledge Discovery

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Data Mining and Knowledge Discovery. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Data Mining and Knowledge Discovery.

About Data Mining and Knowledge Discovery

The 1.2k papers published in Data Mining and Knowledge Discovery in the last decades have received a total of 88.3k indexed citations . Papers published in Data Mining and Knowledge Discovery usually cover Computational Mathematics (17 papers), Signal Processing (165 papers), Artificial Intelligence (546 papers), Information Systems (341 papers) and Statistical and Nonlinear Physics (98 papers) specifically the topics of Data Mining Algorithms and Applications (239 papers), Time Series Analysis and Forecasting (136 papers), Advanced Clustering Algorithms Research (105 papers), Complex Network Analysis Techniques (94 papers), Advanced Graph Neural Networks (68 papers), Anomaly Detection Techniques and Applications (61 papers), Recommender Systems and Techniques (57 papers) and Machine Learning and Data Classification (51 papers). The most active scholars publishing in Data Mining and Knowledge Discovery are Christopher J. C. Burges, Joshua Zhexue Huang, Eamonn Keogh, Jon M. Kleinberg, Jiawei Han, Hannu T. T. Toivonen, Jerome H. Friedman, Sreerama K. Murthy, Heikki Mannila and Steven L. Salzberg.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore journals with similar magnitude of impact