Mario Graff
Impact in
- Artificial Intelligence top 5%
- Metaheuristic Optimization Algorithms Research
- Sentiment Analysis and Opinion Mining
- Evolutionary Algorithms and Applications
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Topic Modeling
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- Stock Market Forecasting Methods
Papers in
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- Evolutionary Algorithms and Applications 32
- Metaheuristic Optimization Algorithms Research 27
- Sentiment Analysis and Opinion Mining 10
- Neural Networks and Applications 9
- Advanced Text Analysis Techniques 7
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- Stock Market Forecasting Methods 8
- Co-authors
- Eric S. Téllez (33 shared papers)Riccardo Poli (10 shared papers)Juan J. Flores (12 shared papers)Sabino Miranda‐Jiménez (22 shared papers)Hugo Jair Escalante (12 shared papers)Daniela Moctezuma (21 shared papers)Héctor Rodríguez (3 shared papers)Raúl Oramas Bustillos (1 shared paper)
- Journals
- Natural Computing (2 papers)Expert Systems with Applications (2 papers)Renewable Energy (2 papers)Lecture notes in computer science (13 papers)Pattern Recognition Letters (1 paper)
- Partner nations
- MexicoUnited KingdomSpain
In The Last Decade
Mario Graff
81 papers receiving 783 citations
Peers
Comparison fields: 5 of 114
- Artificial Intelligence 553
- Management Science and Operations Research 88
- Computer Science Applications 34
- Signal Processing 52
- Information Systems 96
Countries citing papers authored by Mario Graff
This map shows the geographic impact of Mario Graff'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 Mario Graff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mario Graff more than expected).
Fields of papers citing papers by Mario Graff
This network shows the impact of papers produced by Mario Graff. 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 Mario Graff. The network helps show where Mario Graff may publish in the future.
Co-authors
The 25 scholars most cited alongside Mario Graff, 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 83 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 79 | |
| 2 | 2012 | 66 | |
| 3 | 2015 | 55 | |
| 4 | 2017 | 51 | |
| 5 | 2009 | 37 | |
| 6 | 2017 | 32 | |
| 7 | 2015 | 24 | |
| 8 | 2010 | 22 | |
| 9 | 2013 | 21 | |
| 10 | 2009 | 21 | |
| 11 | 2014 | 18 | |
| 12 | 2015 | 18 | |
| 13 | 2013 | 17 | |
| 14 | 2016 | 17 | |
| 15 | 2016 | 16 | |
| 16 | 2014 | 15 | |
| 17 | 2018 | 15 | |
| 18 | 2009 | 14 | |
| 19 | 2015 | 13 | |
| 20 | 2016 | 13 |
About Mario Graff
Mario Graff is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Signal Processing, having authored 83 papers that have together received 823 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (32 papers), Metaheuristic Optimization Algorithms Research (27 papers), Sentiment Analysis and Opinion Mining (10 papers), Neural Networks and Applications (9 papers), Stock Market Forecasting Methods (8 papers), Advanced Multi-Objective Optimization Algorithms (8 papers), Advanced Text Analysis Techniques (7 papers) and Energy Load and Power Forecasting (6 papers). The work is most often cited by research in Artificial Intelligence (553 citations), Management Science and Operations Research (88 citations), Computer Science Applications (34 citations), Signal Processing (52 citations) and Information Systems (96 citations). Mario Graff has collaborated with scholars based in Mexico, United Kingdom and Spain. Frequent co-authors include Eric S. Téllez, Riccardo Poli, Juan J. Flores, Sabino Miranda‐Jiménez, Hugo Jair Escalante, Daniela Moctezuma, Héctor Rodríguez, Raúl Oramas Bustillos, María Lucía Barrón Estrada and Ramón Zataraín Cabada. Their work appears in journals such as Natural Computing, Expert Systems with Applications, Renewable Energy, Lecture notes in computer science and Pattern Recognition Letters.
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.