International Journal of Data Warehousing and Mining

326 papers and 3.2k indexed citations i.

About

The 326 papers published in International Journal of Data Warehousing and Mining in the last decades have received a total of 3.2k indexed citations. Papers published in International Journal of Data Warehousing and Mining usually cover Artificial Intelligence (147 papers), Information Systems (144 papers) and Signal Processing (111 papers) specifically the topics of Data Management and Algorithms (98 papers), Data Mining Algorithms and Applications (92 papers) and Advanced Database Systems and Queries (87 papers). The most active scholars publishing in International Journal of Data Warehousing and Mining are Ioannis Katakis, Grigorios Tsoumakas, Panos Vassiliadis, Matteo Golfarelli, Stefano Rizzi, David Taniar, Shuliang Wang, Alberto Abelló, Oscar Romero and Seifedine Kadry.

In The Last Decade

Fields of papers published in International Journal of Data Warehousing and Mining

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in International Journal of Data Warehousing and Mining. 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 International Journal of Data Warehousing and Mining.

Countries where authors publish in International Journal of Data Warehousing and Mining

Since Specialization
Citations

This map shows the geographic impact of research published in International Journal of Data Warehousing and Mining. 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 International Journal of Data Warehousing and Mining with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites International Journal of Data Warehousing and Mining 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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2025