Juan Bernabé-Moreno
- Artificial Intelligence top 5%
- Information Systems top 5%
- Management Science and Operations Research top 10%
- Sociology and Political Science
- Computer Vision and Pattern Recognition
- Co-authors
- Enrique Herrera‐ViedmaCarlos PorcelÁlvaro Tejeda-LorenteCarmen Martínez-CruzHamido FujitaG. CortianaMartin FischerRam Rajagopal
- Topics
- Recommender Systems and Techniques (10 papers)Advanced Text Analysis Techniques (5 papers)Topic Modeling (4 papers)
- Partner nations
- SpainJapanUnited States
In The Last Decade
Juan Bernabé-Moreno
31 papers receiving 453 citations
Peers
Comparison fields: 5 of 78
- Artificial Intelligence 226
- Information Systems 222
- Management Science and Operations Research 69
- Sociology and Political Science 66
- Computer Vision and Pattern Recognition 57
Countries citing papers authored by Juan Bernabé-Moreno
This map shows the geographic impact of Juan Bernabé-Moreno'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 Juan Bernabé-Moreno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Juan Bernabé-Moreno more than expected).
Fields of papers citing papers by Juan Bernabé-Moreno
This network shows the impact of papers produced by Juan Bernabé-Moreno. 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 Juan Bernabé-Moreno. The network helps show where Juan Bernabé-Moreno may publish in the future.
Co-authorship network of co-authors of Juan Bernabé-Moreno
This figure shows the co-authorship network connecting the top 25 collaborators of Juan Bernabé-Moreno. A scholar is included among the top collaborators of Juan Bernabé-Moreno 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 Juan Bernabé-Moreno. Juan Bernabé-Moreno 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 | 3 | |
| 3 | 28 | |
| 4 | 4 | |
| 5 | 16 | |
| 6 | 6 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 10 | |
| 10 | 15 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 7 | |
| 14 | 7 | |
| 15 | 31 | |
| 16 | 21 | |
| 17 | 5 | |
| 18 | 36 | |
| 19 | 7 | |
| 20 | 2 |
About Juan Bernabé-Moreno
Juan Bernabé-Moreno is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research, having authored 31 papers that have together received 469 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (10 papers), Advanced Text Analysis Techniques (5 papers) and Topic Modeling (4 papers). The work is most often cited by research in Information Systems (222 citations), Artificial Intelligence (226 citations) and Computational Mathematics (4 citations). Juan Bernabé-Moreno has collaborated with scholars based in Spain, Japan and United States. Frequent co-authors include Enrique Herrera‐Viedma, Carlos Porcel, Álvaro Tejeda-Lorente, Carmen Martínez-Cruz, Hamido Fujita, G. Cortiana, Martin Fischer, Ram Rajagopal, Pablo Galindo‐Moreno and Christian B. Mendl. Their work appears in journals such as Applied Energy, Expert Systems with Applications and Information Sciences.
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.