Ines Färber

6 papers and 52 indexed citations i.

About

Ines Färber is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ines Färber has authored 6 papers receiving a total of 52 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 4 papers in Information Systems and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ines Färber’s work include Advanced Clustering Algorithms Research (4 papers), Data Mining Algorithms and Applications (3 papers) and Digitalization, Law, and Regulation (2 papers). Ines Färber is often cited by papers focused on Advanced Clustering Algorithms Research (4 papers), Data Mining Algorithms and Applications (3 papers) and Digitalization, Law, and Regulation (2 papers). Ines Färber collaborates with scholars based in Germany, Denmark and United States. Ines Färber's co-authors include Stephan Günnemann, Thomas Seidl, Brigitte Boden, Ira Assent, Emmanuel Müller, Hardy Kremer, Johannes Merkle, Xuebing Zhou, Christoph Busch and Christian Böhm and has published in prestigious journals such as Proceedings of the VLDB Endowment, Knowledge and Information Systems and Research Portal Denmark.

In The Last Decade

Co-authorship network of co-authors of Ines Färber i

Fields of papers citing papers by Ines Färber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ines Färber. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ines Färber. The network helps show where Ines Färber may publish in the future.

Countries citing papers authored by Ines Färber

Since Specialization
Citations

This map shows the geographic impact of Ines Färber's research. 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 Ines Färber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ines Färber 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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