Juan Bernabé-Moreno

776 total citations
31 papers, 469 citations indexed

About

Juan Bernabé-Moreno is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research. According to data from OpenAlex, Juan Bernabé-Moreno has authored 31 papers receiving a total of 469 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 13 papers in Information Systems and 7 papers in Management Science and Operations Research. Recurrent topics in Juan Bernabé-Moreno's work include Recommender Systems and Techniques (10 papers), Advanced Text Analysis Techniques (5 papers) and Topic Modeling (4 papers). Juan Bernabé-Moreno is often cited by papers focused on Recommender Systems and Techniques (10 papers), Advanced Text Analysis Techniques (5 papers) and Topic Modeling (4 papers). Juan Bernabé-Moreno collaborates with scholars based in Spain, Japan and United States. Juan Bernabé-Moreno's 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 and has published in prestigious journals such as Applied Energy, Expert Systems with Applications and Information Sciences.

In The Last Decade

Juan Bernabé-Moreno

31 papers receiving 453 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Juan Bernabé-Moreno Spain 12 226 222 69 66 57 31 469
Bharat Bhasker India 10 191 0.8× 240 1.1× 53 0.8× 87 1.3× 58 1.0× 40 464
Fernando Mourão Brazil 12 274 1.2× 256 1.2× 46 0.7× 60 0.9× 62 1.1× 50 508
Sujoy Bag India 7 173 0.8× 211 1.0× 60 0.9× 79 1.2× 88 1.5× 9 436
Álvaro Tejeda-Lorente Spain 11 256 1.1× 338 1.5× 108 1.6× 81 1.2× 87 1.5× 22 569
Jinghua Piao China 9 277 1.2× 217 1.0× 30 0.4× 55 0.8× 75 1.3× 13 470
Yi Cai China 17 419 1.9× 203 0.9× 136 2.0× 77 1.2× 66 1.2× 58 792
Ahmad Baraani-Dastjerdi Iran 13 256 1.1× 168 0.8× 68 1.0× 75 1.1× 32 0.6× 52 544
Maryam Khanian Najafabadi Malaysia 7 164 0.7× 298 1.3× 49 0.7× 70 1.1× 64 1.1× 23 507
Albert Weichselbraun Austria 14 471 2.1× 192 0.9× 60 0.9× 111 1.7× 74 1.3× 67 700
Thomas Steiner Spain 13 275 1.2× 187 0.8× 60 0.9× 91 1.4× 106 1.9× 53 561

Countries citing papers authored by Juan Bernabé-Moreno

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Bernabé-Moreno, Juan, et al.. (2025). An Innovative Hybrid Soft Consensus Framework Leveraging Generative Large Language Models and Human Expertise. Proceedings of the ... Annual Hawaii International Conference on System Sciences. 1 indexed citations
2.
Fraccaro, Paolo, Johannes Jakubik, Gabriele Cavallaro, et al.. (2025). Terramesh: A Planetary Mosaic of Multimodal Earth Observation Data. 2385–2393. 1 indexed citations
3.
Bernabé-Moreno, Juan, et al.. (2024). Energy Risk Analysis With Dynamic Amplitude Estimation and Piecewise Approximate Quantum Compiling. IEEE Transactions on Quantum Engineering. 5. 1–17. 3 indexed citations
4.
Bernabé-Moreno, Juan, et al.. (2023). Estimating building energy efficiency from street view imagery, aerial imagery, and land surface temperature data. Applied Energy. 333. 120542–120542. 28 indexed citations
5.
6.
Porcel, Carlos, et al.. (2022). Introducing CSP Dataset: A Dataset Optimized for the Study of the Cold Start Problem in Recommender Systems. Information. 14(1). 19–19. 6 indexed citations
7.
Mendl, Christian B., et al.. (2022). Hybrid classical-quantum autoencoder for anomaly detection. Quantum Machine Intelligence. 4(2). 16 indexed citations
8.
Bernabé-Moreno, Juan. (2022). When digitalization becomes an essential part of our energy transition. 6(2). 8–13. 3 indexed citations
9.
Cortiana, G., et al.. (2022). Practical Quantum K-Means Clustering: Performance Analysis and Applications in Energy Grid Classification. IEEE Transactions on Quantum Engineering. 3. 1–16. 10 indexed citations
10.
Schlüter, Alexander & Juan Bernabé-Moreno. (2022). Sustainable and Smart Energy Systems for Europe’s Cities and Rural Areas. 1 indexed citations
11.
Porcel, Carlos, et al.. (2020). Trust Based Fuzzy Linguistic Recommender Systems as Reinforcement for Personalized Education in the Field of Oral Surgery and Implantology. International Journal of Computers Communications & Control. 15(3). 1 indexed citations
12.
Porcel, Carlos, et al.. (2019). Web platform for learning distributed databases’ queries processing. Procedia Computer Science. 162. 827–834. 1 indexed citations
13.
Bernabé-Moreno, Juan, et al.. (2019). An automatic skills standardization method based on subject expert knowledge extraction and semantic matching. Procedia Computer Science. 162. 857–864. 7 indexed citations
14.
Tejeda-Lorente, Álvaro, et al.. (2019). A risk-aware fuzzy linguistic knowledge-based recommender system for hedge funds. Procedia Computer Science. 162. 916–923. 7 indexed citations
15.
Bernabé-Moreno, Juan, Álvaro Tejeda-Lorente, Carlos Porcel, Hamido Fujita, & Enrique Herrera‐Viedma. (2018). Quantifying the emotional impact of events on locations with social media. Knowledge-Based Systems. 146. 44–57. 21 indexed citations
16.
Porcel, Carlos, et al.. (2017). Fuzzy Linguistic Recommender Systems for the Selective Diffusion of Information in Digital Libraries. Journal of Information Processing Systems. 5 indexed citations
17.
Martínez-Cruz, Carmen, Carlos Porcel, Juan Bernabé-Moreno, & Enrique Herrera‐Viedma. (2015). A model to represent users trust in recommender systems using ontologies and fuzzy linguistic modeling. Information Sciences. 311. 102–118. 100 indexed citations
18.
Bernabé-Moreno, Juan, Álvaro Tejeda-Lorente, Carlos Porcel, Hamido Fujita, & Enrique Herrera‐Viedma. (2015). Emotional Profiling of Locations Based on Social Media. Procedia Computer Science. 55. 960–969. 8 indexed citations
19.
Bernabé-Moreno, Juan, Álvaro Tejeda-Lorente, Carlos Porcel, & Enrique Herrera‐Viedma. (2014). Leveraging Localized Social Media Insights for Early Warning Systems. Procedia Computer Science. 31. 1051–1060. 2 indexed citations
20.
Tejeda-Lorente, Álvaro, Juan Bernabé-Moreno, Carlos Porcel, & Enrique Herrera‐Viedma. (2014). Integrating Quality Criteria in a Fuzzy Linguistic Recommender System for Digital Libraries. Procedia Computer Science. 31. 1036–1043. 7 indexed citations

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.

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