Boris Čule
Impact in
- Signal Processing top 10%
- Time Series Analysis and Forecasting
- Data Management and Algorithms
- Health Information Management top 10%
Papers in
-
- Data Management and Algorithms 6
- Time Series Analysis and Forecasting 2
-
- Data Mining Algorithms and Applications 11
- Co-authors
- Bart GoethalsCheng ZhouPieter MeysmanKris LaukensNikolaj TattiKim LuyckxWalter DaelemansPieter Moris
- Journals
- BioData Mining (2 papers)Data Mining and Knowledge Discovery (2 papers)IEEE/ACM Transactions on Computational Biology and Bioinformatics (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)Journal of Biomedical Informatics (1 paper)
- Partner nations
- BelgiumNetherlandsAustralia
In The Last Decade
Boris Čule
22 papers receiving 193 citations
Peers
Comparison fields: 5 of 58
- Signal Processing 69
- Health Information Management 16
- Information Systems 75
- Artificial Intelligence 106
- Computer Vision and Pattern Recognition 33
Countries citing papers authored by Boris Čule
This map shows the geographic impact of Boris Čule'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 Boris Čule with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Boris Čule more than expected).
Fields of papers citing papers by Boris Čule
This network shows the impact of papers produced by Boris Čule. 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 Boris Čule. The network helps show where Boris Čule may publish in the future.
Co-authorship network
The 17 scholars most cited alongside Boris Čule, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2024 | 2 | |
| 3 | 2023 | 4 | |
| 4 | 2023 | 2 | |
| 5 | 2022 | 5 | |
| 6 | 2022 | 1 | |
| 7 | 2022 | 17 | |
| 8 | 2020 | 4 | |
| 9 | 2019 | 3 | |
| 10 | 2018 | 30 | |
| 11 | 2017 | 35 | |
| 12 | 2017 | 1 | |
| 13 | 2017 | 2 | |
| 14 | 2015 | 12 | |
| 15 | 2015 | 16 | |
| 16 | 2015 | 35 | |
| 17 | 2014 | 5 | |
| 18 | 2013 | 9 | |
| 19 | 2012 | 1 | |
| 20 | 2010 | 10 |
About Boris Čule
Boris Čule is a scholar working on Signal Processing, Information Systems, Computational Theory and Mathematics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 22 papers that have together received 203 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (11 papers), Data Management and Algorithms (6 papers), Rough Sets and Fuzzy Logic (5 papers), Advanced Database Systems and Queries (4 papers), Advanced Proteomics Techniques and Applications (2 papers), Time Series Analysis and Forecasting (2 papers), Bioinformatics and Genomic Networks (2 papers) and Robotic Path Planning Algorithms (2 papers). The work is most often cited by research in Signal Processing (69 citations), Health Information Management (16 citations), Information Systems (75 citations), Artificial Intelligence (106 citations) and Computer Vision and Pattern Recognition (33 citations). Boris Čule has collaborated with scholars based in Belgium, Netherlands and Australia. Frequent co-authors include Bart Goethals, Cheng Zhou, Pieter Meysman, Kris Laukens, Nikolaj Tatti, Kim Luyckx, Walter Daelemans, Pieter Moris, Wout Bittremieux and Celine Vens. Their work appears in journals such as BioData Mining, Data Mining and Knowledge Discovery, IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Transactions on Knowledge and Data Engineering and Journal of Biomedical Informatics.
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.