Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery

495 papers and 21.3k indexed citations i.

About

The 495 papers published in Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery in the last decades have received a total of 21.3k indexed citations. Papers published in Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery usually cover Artificial Intelligence (291 papers), Information Systems (143 papers) and Signal Processing (81 papers) specifically the topics of Data Mining Algorithms and Applications (78 papers), Data Management and Algorithms (49 papers) and Machine Learning and Data Classification (43 papers). The most active scholars publishing in Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery are Wei‐Yin Loh, Lior Rokach, Anne‐Laure Boulesteix, Pedro Contreras, Fionn Murtagh, Sebastián Ventura, Cristóbal Romero, Marvin N. Wright, Philipp Probst and Mia Hubert.

In The Last Decade

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.

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).

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.

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