Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery

25.7k citations
513 papers · · active since 1950

Impact in

Papers in

Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery

471 papers receiving 24.3k citations

Peers

Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
Comparison fields: 5 of 239
  • Health Informatics 664
  • Computational Mathematics 211
  • Artificial Intelligence 10.4k
  • Computer Science Applications 1.5k
  • Information Systems 4.2k
Replace Computer Science Review with:
Computer Science Review India
ACM Transactions on Interactive Intelligent Systems United States
User Modeling and User-Adapted Interaction United States
ACM Transactions on Internet Technology United States
Wiley Interdisciplinary Reviews Computational Statistics United States
Transactions of the Association for Computational Linguistics United States
IEEE Computational Intelligence Magazine China
The Knowledge Engineering Review United Kingdom
Natural Language Engineering United States
AI Communications Spain
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery relative to Computer Science Review India Computer Science Review's profile →
Citations per field
00.5×9.2×
Computer Science Review · 1×
Citations per year

Countries where authors publish in Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery

Since Specialization
Citations

This map shows the geographic impact of research published in Wiley Interdisciplinary Reviews 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 Wiley Interdisciplinary Reviews 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 Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery more than expected).

Fields of papers published in Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Wiley Interdisciplinary Reviews 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 Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery.

About Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery

The 513 papers published in Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery in the last decades have received a total of 25.7k indexed citations . Papers published in Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery usually cover Computational Mathematics (6 papers), Artificial Intelligence (299 papers), Signal Processing (83 papers), Health Informatics (9 papers) and Information Systems (145 papers) specifically the topics of Data Mining Algorithms and Applications (78 papers), Data Management and Algorithms (50 papers), Machine Learning and Data Classification (43 papers), Data Stream Mining Techniques (35 papers), Advanced Clustering Algorithms Research (35 papers), Rough Sets and Fuzzy Logic (33 papers), Complex Network Analysis Techniques (32 papers) and Imbalanced Data Classification Techniques (24 papers). The most active scholars publishing in Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery are Wei‐Yin Loh, Lior Rokach, Sebastián Ventura, Fionn Murtagh, Pedro Contreras, Cristóbal Romero, Lei Zhang, Shuai Wang, Bing Liu and Inke R. König.

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