Bernard Ženko
Impact in
- Artificial Intelligence top 2%
- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
- Anomaly Detection Techniques and Applications
- Data Stream Mining Techniques
- Text and Document Classification Technologies
Papers in
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- Machine Learning and Data Classification 6
- Imbalanced Data Classification Techniques 3
- Co-authors
- Sašo Džeroski (17 shared papers)Monika Novak Babič (2 shared papers)Nina Gunde‐Cimerman (2 shared papers)Polona Zalar (2 shared papers)Tapio Elomaa (1 shared paper)Timo Aho (1 shared paper)Ljupčo Todorovski (3 shared papers)Maja Rupnik (2 shared papers)
In The Last Decade
Bernard Ženko
29 papers receiving 1.2k citations
Bernard Ženko's Hit Papers
Peers
Comparison fields: 5 of 170
- Artificial Intelligence 532
- Health Information Management 41
- Signal Processing 83
- Computer Vision and Pattern Recognition 139
- Information Systems 124
Countries citing papers authored by Bernard Ženko
This map shows the geographic impact of Bernard Ženko'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 Bernard Ženko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bernard Ženko more than expected).
Fields of papers citing papers by Bernard Ženko
This network shows the impact of papers produced by Bernard Ženko. 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 Bernard Ženko. The network helps show where Bernard Ženko may publish in the future.
Co-authors
The 25 scholars most cited alongside Bernard Ženko, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Is Combining Classifiers with Stacking Better than Selecting the Best One? Hit paper breakdown → | 2004 | 595 |
| 2 | 2015 | 74 | |
| 3 | Multi-target regression with rule ensembles | 2012 | 73 |
| 4 | Is Combining Classifiers Better than Selecting the Best One | 2002 | 66 |
| 5 | 2013 | 62 | |
| 6 | 2015 | 61 | |
| 7 | 2002 | 38 | |
| 8 | 2011 | 38 | |
| 9 | 2006 | 25 | |
| 10 | Speeding-Up Hoeffding-Based Regression Trees With Options | 2011 | 25 |
| 11 | 2013 | 23 | |
| 12 | 2017 | 21 | |
| 13 | 2018 | 20 | |
| 14 | 2016 | 19 | |
| 15 | 2014 | 18 | |
| 16 | 2006 | 13 | |
| 17 | 2019 | 13 | |
| 18 | 2016 | 11 | |
| 19 | Evaluation Method for Feature Rankings and their Aggregations for Biomarker Discovery | 2009 | 11 |
| 20 | 2019 | 10 |
About Bernard Ženko
Bernard Ženko is a scholar working on Artificial Intelligence, Molecular Biology, Information Systems, Health, Toxicology and Mutagenesis and Infectious Diseases, having authored 31 papers that have together received 1.3k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (6 papers), Data Mining Algorithms and Applications (5 papers), Imbalanced Data Classification Techniques (3 papers), Plant Pathogens and Fungal Diseases (2 papers), Alzheimer's disease research and treatments (2 papers), Spacecraft Design and Technology (2 papers), Dementia and Cognitive Impairment Research (2 papers) and Aging, Elder Care, and Social Issues (2 papers). The work is most often cited by research in Artificial Intelligence (532 citations), Health Information Management (41 citations), Signal Processing (83 citations), Computer Vision and Pattern Recognition (139 citations) and Information Systems (124 citations). Bernard Ženko has collaborated with scholars based in Slovenia, Croatia and Germany. Frequent co-authors include Sašo Džeroski, Monika Novak Babič, Nina Gunde‐Cimerman, Polona Zalar, Tapio Elomaa, Timo Aho, Ljupčo Todorovski, Maja Rupnik, Hans‐Josef Schroers and Domen Mongus. Their work appears in journals such as Food Chemistry, Ecological Indicators, Data Mining and Knowledge Discovery, Brain Informatics and Fungal Biology.
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.