Grigorios Tsoumakas
- Artificial Intelligence top 0.1%
- Computer Vision and Pattern Recognition top 0.5%
- Information Systems top 0.5%
- Molecular Biology top 10%
- Signal Processing top 1%
- Co-authors
- Ioannis KatakisIoannis VlahavasGeorge KallirisEleftherios Spyromitros-XioufisJozef VilčekBin LiuIoannis PartalasIoannis Kompatsiaris
- Topics
- Text and Document Classification Technologies (34 papers)Topic Modeling (24 papers)Advanced Text Analysis Techniques (20 papers)
In The Last Decade
Grigorios Tsoumakas
114 papers receiving 5.2k citations
Hit Papers
Peers
Comparison fields: 5 of 166
- Artificial Intelligence 4.1k
- Computer Vision and Pattern Recognition 1.6k
- Information Systems 1.4k
- Molecular Biology 872
- Signal Processing 483
Countries citing papers authored by Grigorios Tsoumakas
This map shows the geographic impact of Grigorios Tsoumakas'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 Grigorios Tsoumakas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Grigorios Tsoumakas more than expected).
Fields of papers citing papers by Grigorios Tsoumakas
This network shows the impact of papers produced by Grigorios Tsoumakas. 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 Grigorios Tsoumakas. The network helps show where Grigorios Tsoumakas may publish in the future.
Co-authorship network of co-authors of Grigorios Tsoumakas
This figure shows the co-authorship network connecting the top 25 collaborators of Grigorios Tsoumakas. A scholar is included among the top collaborators of Grigorios Tsoumakas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Grigorios Tsoumakas. Grigorios Tsoumakas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | 4 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 15 | |
| 10 | 4 | |
| 11 | 58 | |
| 12 | 5 | |
| 13 | 12 | |
| 14 | 33 | |
| 15 | 33 | |
| 16 | 58 | |
| 17 | Making Classifier Chains Resilient to Class Imbalance | 2 |
| 18 | 12 | |
| 19 | 70 | |
| 20 | 1 |
About Grigorios Tsoumakas
Grigorios Tsoumakas is a scholar working on Artificial Intelligence, Signal Processing and Information Systems, having authored 121 papers that have together received 5.4k indexed citations. Recurring topics across this work include Text and Document Classification Technologies (34 papers), Topic Modeling (24 papers) and Advanced Text Analysis Techniques (20 papers). The work is most often cited by research in Artificial Intelligence (4.1k citations), Computer Vision and Pattern Recognition (1.6k citations) and Information Systems (1.4k citations). Grigorios Tsoumakas has collaborated with scholars based in Greece, France and Belgium. Frequent co-authors include Ioannis Katakis, Ioannis Vlahavas, George Kalliris, Eleftherios Spyromitros-Xioufis, Jozef Vilček, Bin Liu, Ioannis Partalas, Ioannis Kompatsiaris, Nick Bassiliades and Lefteris Angelis. Their work appears in journals such as Expert Systems with Applications, IEEE Access and BMC Bioinformatics.
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.