Sašo Džeroski

19.4k citations
327 papers · 9.4k indexed · 3 hit papers · h-index 46
Topics
Data Mining Algorithms and Applications (48 papers)Machine Learning and Data Classification (34 papers)Rough Sets and Fuzzy Logic (27 papers)
Journals
Nature CommunicationsSHILAP Revista de lepidopterologíaPLoS ONE
Partner nations
SloveniaGermanyBelgium

In The Last Decade

Sašo Džeroski

315 papers receiving 8.8k citations

Hit Papers

Is Combining Classifiers with Stacking Better than Select...2004202620112018200420122005100200300400500

Peers

Sašo Džeroski
Comparison fields: 5 of 216
  • Artificial Intelligence 4.9k
  • Information Systems 1.5k
  • Molecular Biology 1.4k
  • Computer Vision and Pattern Recognition 1.1k
  • Computational Theory and Mathematics 984
Replace M. Anthony Wong with:
M. Anthony Wong United States
Nathan S. Netanyahu United States
Lizhe Wang China
Carla E. Brodley United States
Kim H. Esbensen Denmark
Geoffrey I. Webb Australia
Rich Caruana United States
Nikhil R. Pal India
Sotiris Kotsiantis Greece
Jianchang Mao United States
Sašo Džeroski relative to M. Anthony Wong United States M. Anthony Wong's profile →
Citations per field
00.5×2.9×
M. Anthony Wong · 1×
Citations per year

Countries citing papers authored by Sašo Džeroski

Since Specialization
Citations

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

Fields of papers citing papers by Sašo Džeroski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sašo Džeroski. 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 Sašo Džeroski. The network helps show where Sašo Džeroski may publish in the future.

Co-authorship network of co-authors of Sašo Džeroski

This figure shows the co-authorship network connecting the top 25 collaborators of Sašo Džeroski. A scholar is included among the top collaborators of Sašo Džeroski 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 Sašo Džeroski. Sašo Džeroski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 8
4 2
5 6
6 4
7 5
8 2
9 5
10 5
11 10
12 2
13 1
14 2
15 6
16 6
17 35
18 5
19 18
20 8

About Sašo Džeroski

Sašo Džeroski is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems, having authored 327 papers that have together received 9.4k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (48 papers), Machine Learning and Data Classification (34 papers) and Rough Sets and Fuzzy Logic (27 papers). The work is most often cited by research in Artificial Intelligence (4.9k citations), Information Systems (1.5k citations) and Computational Theory and Mathematics (984 citations). Sašo Džeroski has collaborated with scholars based in Slovenia, Germany and Belgium. Frequent co-authors include Bernard Ženko, Dragi Kocev, Ljupčo Todorovski, Nada Lavrač, Luc De Raedt, Jan Struyf, Celine Vens, Hendrik Blockeel, Stefan Wrobel and Gjorgji Madjarov. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

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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