Cristóbal Romero
About
In The Last Decade
Cristóbal Romero
98 papers receiving 8.1k citations
Hit Papers
Peers
Comparison fields: 5 of 161
- Computer Science Applications 5.8k
- Artificial Intelligence 4.2k
- Information Systems 2.9k
- Education 1.4k
- Computer Networks and Communications 960
Countries citing papers authored by Cristóbal Romero
This map shows the geographic impact of Cristóbal Romero'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 Cristóbal Romero with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cristóbal Romero more than expected).
Fields of papers citing papers by Cristóbal Romero
This network shows the impact of papers produced by Cristóbal Romero. 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 Cristóbal Romero. The network helps show where Cristóbal Romero may publish in the future.
Co-authorship network of co-authors of Cristóbal Romero
This figure shows the co-authorship network connecting the top 25 collaborators of Cristóbal Romero. A scholar is included among the top collaborators of Cristóbal Romero 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 Cristóbal Romero. Cristóbal Romero is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 19 | |
| 2 | 106 | |
| 3 | 8 | |
| 4 | 11 | |
| 5 | A Hybrid Multi-Criteria Approach Using a Genetic Algorithm for Recommending Courses to University Students. | 13 |
| 6 | Towards Automatic Classification of Learning Objects: Reducing the Number of Used Features. | 2 |
| 7 | 200 | |
| 8 | Accepting or Rejecting Students_ Self-grading in their Final Marks by using Data Mining. | 2 |
| 9 | A meta-learning approach for recommending a subset of white-box classification algorithms for Moodle datasets. | 19 |
| 10 | Classification via clustering for predicting final marks starting from the student participation in Forums. | 19 |
| 11 | Classification via Clustering for Predicting Final Marks Based on Student Participation in Forums. | 78 |
| 12 | Using Data Mining in a Recommender System to Search for Learning Objects in Repositories. | 4 |
| 13 | A Java Desktop Tool for Mining Moodle Data | 17 |
| 14 | Class Association Rules Mining from Students' Test Data. | 10 |
| 15 | Proceedings of the International Conference on Educational Data Mining (EDM) (2nd, Cordoba, Spain, July 1-3, 2009). | 2 |
| 16 | Collaborative Data Mining Tool for Education | 7 |
| 17 | Mining and visualizing visited trails in web-based educational systems | 31 |
| 18 | Herramienta Autor para la Gestión de Tests Informatizados dentro del Sistema AHA | 1 |
| 19 | An authoring tool for web-based adaptive and classic tests | 3 |
| 20 | Herramienta autor indesahc para la creación de cursos hipermedia adaptativos | 4 |
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.