Carlos Molina
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Information Systems top 10%
- Computer Networks and Communications
- Computational Theory and Mathematics
- Co-authors
- M.A. VilaNéstor Becerra YomaDaniel SánchezNicolás Marı́nJosé-Marı́a SerranoFernando HuenupánLázaro Rodríguez ArizaCarlos Rodríguez
- Topics
- Data Mining Algorithms and Applications (14 papers)Speech Recognition and Synthesis (9 papers)Rough Sets and Fuzzy Logic (9 papers)
In The Last Decade
Carlos Molina
42 papers receiving 207 citations
Peers
Comparison fields: 5 of 68
- Artificial Intelligence 118
- Signal Processing 66
- Information Systems 65
- Computer Networks and Communications 31
- Computational Theory and Mathematics 30
Countries citing papers authored by Carlos Molina
This map shows the geographic impact of Carlos Molina'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 Carlos Molina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carlos Molina more than expected).
Fields of papers citing papers by Carlos Molina
This network shows the impact of papers produced by Carlos Molina. 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 Carlos Molina. The network helps show where Carlos Molina may publish in the future.
Co-authorship network of co-authors of Carlos Molina
This figure shows the co-authorship network connecting the top 25 collaborators of Carlos Molina. A scholar is included among the top collaborators of Carlos Molina 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 Carlos Molina. Carlos Molina 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 | 1 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 25 | |
| 7 | Reducción de Redundancia en Reglas de Asociación | 1 |
| 8 | 3 | |
| 9 | Semantically-driven flexible division in fuzzy object oriented models | 2 |
| 10 | Managing the Absence of Items in Fuzzy Association Mining | 1 |
| 11 | 14 | |
| 12 | 1 | |
| 13 | 17 | |
| 14 | Measuring Variation Strength in Gradual Dependencies. | 9 |
| 15 | What the public sector should know about venture capital. | 1 |
| 16 | 0 | |
| 17 | Using Fuzzy DataCube for Exploratory Analysis in Financial Economy. | 1 |
| 18 | 11 | |
| 19 | [Pulmonary reactions to non-infective antigenic contaminants]. | 1 |
| 20 | [Asthma in the course of bronchopulmonary allergic reactions due to precipitins]. | 1 |
About Carlos Molina
Carlos Molina is a scholar working on Signal Processing, Information Systems and Artificial Intelligence, having authored 47 papers that have together received 224 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (14 papers), Speech Recognition and Synthesis (9 papers) and Rough Sets and Fuzzy Logic (9 papers). The work is most often cited by research in Signal Processing (66 citations), Artificial Intelligence (118 citations) and Information Systems (65 citations). Carlos Molina has collaborated with scholars based in Spain, Chile and Cuba. Frequent co-authors include M.A. Vila, Néstor Becerra Yoma, Daniel Sánchez, Nicolás Marı́n, José-Marı́a Serrano, Fernando Huenupán, Lázaro Rodríguez Ariza, Carlos Rodríguez, L. Rajendran and María Martínez‐Rojas. Their work appears in journals such as Expert Systems with Applications, IEEE Transactions on Fuzzy Systems and Fuzzy Sets and 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.