L. Borrajo
Impact in
- Artificial Intelligence top 10%
- Text and Document Classification Technologies
- Topic Modeling
- Advanced Text Analysis Techniques
- AI in cancer detection
- Imbalanced Data Classification Techniques
Papers in
-
- Text and Document Classification Technologies 12
- Topic Modeling 6
- AI-based Problem Solving and Planning 5
- Advanced Text Analysis Techniques 5
- Semantic Web and Ontologies 4
- Imbalanced Data Classification Techniques 3
- Co-authors
- Eva Iglesias (22 shared papers)Juan M. Corchado (4 shared papers)Javier Bajo (2 shared papers)Emilio Corchado (1 shared paper)Bruno Baruque (1 shared paper)Rosalía Laza (2 shared papers)Rui Camacho (2 shared papers)Sérgio N. Silva (1 shared paper)
In The Last Decade
L. Borrajo
24 papers receiving 315 citations
Peers
Comparison fields: 5 of 91
- Artificial Intelligence 195
- Computer Vision and Pattern Recognition 69
- Health Informatics 4
- Neurology 21
- Information Systems 53
Countries citing papers authored by L. Borrajo
This map shows the geographic impact of L. Borrajo'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 L. Borrajo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites L. Borrajo more than expected).
Fields of papers citing papers by L. Borrajo
This network shows the impact of papers produced by L. Borrajo. 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 L. Borrajo. The network helps show where L. Borrajo may publish in the future.
Co-authors
The 13 scholars most cited alongside L. Borrajo, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 92 | |
| 2 | 2011 | 32 | |
| 3 | 2014 | 26 | |
| 4 | 2015 | 23 | |
| 5 | 2013 | 17 | |
| 6 | 2022 | 16 | |
| 7 | 2016 | 14 | |
| 8 | 2009 | 14 | |
| 9 | 2011 | 14 | |
| 10 | 2011 | 13 | |
| 11 | 2020 | 9 | |
| 12 | 2014 | 9 | |
| 13 | 2022 | 9 | |
| 14 | 2021 | 6 | |
| 15 | 2009 | 6 | |
| 16 | 2015 | 6 | |
| 17 | 2003 | 5 | |
| 18 | 2021 | 3 | |
| 19 | 2019 | 2 | |
| 20 | Applying Balancing Techniques to Classify Biomedical Documents: An Empirical Study | 2012 | 2 |
About L. Borrajo
L. Borrajo is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Information Systems and Biophysics, having authored 27 papers that have together received 323 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (12 papers), Topic Modeling (6 papers), AI-based Problem Solving and Planning (5 papers), Advanced Text Analysis Techniques (5 papers), Semantic Web and Ontologies (4 papers), Biomedical Text Mining and Ontologies (4 papers), Cell Image Analysis Techniques (3 papers) and Imbalanced Data Classification Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (195 citations), Computer Vision and Pattern Recognition (69 citations), Health Informatics (4 citations), Neurology (21 citations) and Information Systems (53 citations). L. Borrajo has collaborated with scholars based in Spain and Portugal. Frequent co-authors include Eva Iglesias, Juan M. Corchado, Javier Bajo, Emilio Corchado, Bruno Baruque, Rosalía Laza, Rui Camacho, Emilio Corchado, Sérgio N. Silva and Diego Gachet Páez. Their work appears in journals such as Logic Journal of IGPL, Applied Sciences, Information Sciences, Electronics and Knowledge-Based Systems.
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.