Daniela Stojanova
Impact in
- Environmental Engineering top 10%
- Remote Sensing and LiDAR Applications
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- Forest ecology and management
Papers in
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- Machine Learning in Bioinformatics 1
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- Data Mining Algorithms and Applications 2
- Co-authors
- Sašo Džeroski (7 shared papers)Andrej Kobler (2 shared papers)Panče Panov (1 shared paper)Michelangelo Ceci (3 shared papers)Annalisa Appice (2 shared papers)Donato Malerba (2 shared papers)Bernard Ženko (1 shared paper)Marko Bohanec (1 shared paper)
In The Last Decade
Daniela Stojanova
9 papers receiving 310 citations
Peers
Comparison fields: 5 of 76
- Environmental Engineering 125
- Nature and Landscape Conservation 58
- Ecology 108
- Global and Planetary Change 81
- Artificial Intelligence 76
Countries citing papers authored by Daniela Stojanova
This map shows the geographic impact of Daniela Stojanova'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 Daniela Stojanova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Stojanova more than expected).
Fields of papers citing papers by Daniela Stojanova
This network shows the impact of papers produced by Daniela Stojanova. 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 Daniela Stojanova. The network helps show where Daniela Stojanova may publish in the future.
Co-authors
The 11 scholars most cited alongside Daniela Stojanova, 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 | 2010 | 145 | |
| 2 | 2012 | 38 | |
| 3 | 2011 | 38 | |
| 4 | 2013 | 37 | |
| 5 | 2012 | 35 | |
| 6 | 2006 | 13 | |
| 7 | A Qualitative Decision-Support Model for Evaluating Researchers | 2007 | 7 |
| 8 | 2012 | 6 | |
| 9 | Considering Autocorrelation in Predictive Models | 2013 | 2 |
| 10 | Organization of fine root data obtained from minirhizotrons and ingrowth soil cores (how to construct an operational database using MS Access). | 2011 | 1 |
About Daniela Stojanova
Daniela Stojanova is a scholar working on Molecular Biology, Information Systems, Artificial Intelligence, Plant Science and Nature and Landscape Conservation, having authored 10 papers that have together received 322 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (2 papers), Data Mining Algorithms and Applications (2 papers), Complex Network Analysis Techniques (1 paper), Machine Learning in Bioinformatics (1 paper), Fire Detection and Safety Systems (1 paper), Forest ecology and management (1 paper), Computational Drug Discovery Methods (1 paper) and Plant nutrient uptake and metabolism (1 paper). The work is most often cited by research in Environmental Engineering (125 citations), Nature and Landscape Conservation (58 citations), Ecology (108 citations), Global and Planetary Change (81 citations) and Artificial Intelligence (76 citations). Daniela Stojanova has collaborated with scholars based in Slovenia, Italy and France. Frequent co-authors include Sašo Džeroski, Andrej Kobler, Panče Panov, Michelangelo Ceci, Annalisa Appice, Donato Malerba, Bernard Ženko, Marko Bohanec, Marko Debeljak and Aneta Trajanov. Their work appears in journals such as Ecological Informatics, Data Mining and Knowledge Discovery, Ecological Modelling, BMC Bioinformatics and Acta periodica technologica.
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.