Intelligent Data Analysis

1.4k papers and 16.6k indexed citations
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About

The 1.4k papers published in Intelligent Data Analysis in the last decades have received a total of 16.6k indexed citations. Papers published in Intelligent Data Analysis usually cover Artificial Intelligence (938 papers), Information Systems (422 papers) and Signal Processing (293 papers) specifically the topics of Data Mining Algorithms and Applications (295 papers), Rough Sets and Fuzzy Logic (167 papers) and Data Management and Algorithms (159 papers). The most active scholars publishing in Intelligent Data Analysis are Manoranjan Dash, Hua Liu, Nathalie Japkowicz, Juha Vesanto, Philip K. Chan, Ralf Klinkenberg, Tzung‐Pei Hong, João Gama, Steven M. Bay and Mahamed G. H. Omran.

In The Last Decade

Intelligent Data Analysis

1.2k papers receiving 14.3k citations

Fields of papers published in Intelligent Data Analysis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Intelligent Data Analysis. 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 Intelligent Data Analysis.

Countries where authors publish in Intelligent Data Analysis

Since Specialization
Citations

This map shows the geographic impact of research published in Intelligent Data Analysis. 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 Intelligent Data Analysis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Intelligent Data Analysis more than expected).

The class imbalance problem: A systematic study1 1997 2026 2006 2016 1.7k
  1. The class imbalance problem: A systematic study1 (2002)
  2. Feature selection for classification (1997)

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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