Fernando Alva-Manchego
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition
- Information Systems
- General Health Professions
- Human Factors and Ergonomics
- Co-authors
- Lucia SpeciaCarolina ScartonWei XuMounica MaddelaGustavo Henrique PaetzoldAsahi UshioJosé Camacho-ColladosJoachim Bingel
- Topics
- Natural Language Processing Techniques (15 papers)Topic Modeling (14 papers)Text Readability and Simplification (13 papers)
- Journals
- Computational LinguisticsLanguage Resources and EvaluationComputación y Sistemas
- Partner nations
- United KingdomPeruUnited States
In The Last Decade
Fernando Alva-Manchego
20 papers receiving 250 citations
Peers
Comparison fields: 5 of 25
- Artificial Intelligence 255
- Computer Vision and Pattern Recognition 18
- Information Systems 14
- General Health Professions 12
- Human Factors and Ergonomics 12
Countries citing papers authored by Fernando Alva-Manchego
This map shows the geographic impact of Fernando Alva-Manchego'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 Fernando Alva-Manchego with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Alva-Manchego more than expected).
Fields of papers citing papers by Fernando Alva-Manchego
This network shows the impact of papers produced by Fernando Alva-Manchego. 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 Fernando Alva-Manchego. The network helps show where Fernando Alva-Manchego may publish in the future.
Co-authorship network of co-authors of Fernando Alva-Manchego
This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Alva-Manchego. A scholar is included among the top collaborators of Fernando Alva-Manchego 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 Fernando Alva-Manchego. Fernando Alva-Manchego is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 4 | |
| 6 | 5 | |
| 7 | 18 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 3 | |
| 11 | 44 | |
| 12 | Validating Quality Estimation in a Computer-Aided Translation Workflow: Speed, Cost and Quality Trade-off | 1 |
| 13 | 40 | |
| 14 | 64 | |
| 15 | 3 | |
| 16 | Cross-Sentence Transformations in Text Simplification | 8 |
| 17 | 9 | |
| 18 | 21 | |
| 19 | 30 | |
| 20 | Coh-Metrix-Esp: A Complexity Analysis Tool for Documents Written in Spanish. | 8 |
About Fernando Alva-Manchego
Fernando Alva-Manchego is a scholar working on Health Informatics, Artificial Intelligence and General Social Sciences, having authored 22 papers that have together received 271 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (15 papers), Topic Modeling (14 papers) and Text Readability and Simplification (13 papers). The work is most often cited by research in Artificial Intelligence (255 citations), Human Factors and Ergonomics (12 citations) and Health Informatics (4 citations). Fernando Alva-Manchego has collaborated with scholars based in United Kingdom, Peru and United States. Frequent co-authors include Lucia Specia, Carolina Scarton, Wei Xu, Mounica Maddela, Gustavo Henrique Paetzold, Asahi Ushio, José Camacho-Collados, Joachim Bingel, Matthew Shardlow and Antoine Bordes. Their work appears in journals such as Computational Linguistics, Language Resources and Evaluation and Computación y Sistemas.
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.