Luis E. Zárate
Impact in
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- Online Learning and Analytics
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- Stock Market Forecasting Methods
- Forecasting Techniques and Applications
Papers in
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- Semantic Web and Ontologies 9
- Neural Networks and Applications 8
- Fuzzy Logic and Control Systems 7
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- Rough Sets and Fuzzy Logic 31
- Co-authors
- Cristiane Neri Nobre (38 shared papers)Seiji Isotani (2 shared papers)Sérgio M. Dias (20 shared papers)Luciana Oliveira e Silva (1 shared paper)C. Quirós (8 shared papers)J. M. Alameda (8 shared papers)M. Vélez (6 shared papers)J. I. Martı́n (5 shared papers)
In The Last Decade
Luis E. Zárate
110 papers receiving 1000 citations
Peers
Comparison fields: 5 of 120
- Computer Science Applications 134
- Management Science and Operations Research 241
- Artificial Intelligence 367
- Computational Theory and Mathematics 136
- Information Systems 178
Countries citing papers authored by Luis E. Zárate
This map shows the geographic impact of Luis E. Zárate'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 Luis E. Zárate with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luis E. Zárate more than expected).
Fields of papers citing papers by Luis E. Zárate
This network shows the impact of papers produced by Luis E. Zárate. 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 Luis E. Zárate. The network helps show where Luis E. Zárate may publish in the future.
Co-authors
The 25 scholars most cited alongside Luis E. Zárate, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 132 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 167 | |
| 2 | 2018 | 134 | |
| 3 | 2014 | 68 | |
| 4 | 2011 | 63 | |
| 5 | 2014 | 45 | |
| 6 | 2007 | 26 | |
| 7 | 2007 | 25 | |
| 8 | 2005 | 23 | |
| 9 | 2022 | 23 | |
| 10 | 2008 | 23 | |
| 11 | 2009 | 22 | |
| 12 | 2003 | 21 | |
| 13 | 2024 | 16 | |
| 14 | 2023 | 13 | |
| 15 | 2017 | 13 | |
| 16 | 2003 | 12 | |
| 17 | 2012 | 12 | |
| 18 | 2012 | 12 | |
| 19 | 2011 | 11 | |
| 20 | 2018 | 11 |
About Luis E. Zárate
Luis E. Zárate is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Signal Processing and Molecular Biology, having authored 132 papers that have together received 1.1k indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (31 papers), Data Mining Algorithms and Applications (20 papers), Metallurgy and Material Forming (11 papers), Machine Learning in Bioinformatics (10 papers), Data Management and Algorithms (9 papers), Semantic Web and Ontologies (9 papers), Neural Networks and Applications (8 papers) and Fuzzy Logic and Control Systems (7 papers). The work is most often cited by research in Computer Science Applications (134 citations), Management Science and Operations Research (241 citations), Artificial Intelligence (367 citations), Computational Theory and Mathematics (136 citations) and Information Systems (178 citations). Luis E. Zárate has collaborated with scholars based in Brazil, Spain and France. Frequent co-authors include Cristiane Neri Nobre, Seiji Isotani, Sérgio M. Dias, Luciana Oliveira e Silva, C. Quirós, J. M. Alameda, M. Vélez, J. I. Martı́n, Henrique Cota de Freitas and Humberto Rocha. Their work appears in journals such as Expert Systems with Applications, Physical Review B, Journal of Physics Condensed Matter, Engineering Applications of Artificial Intelligence 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.