Mario Graff
Impact in
- Artificial Intelligence top 5%
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Evolutionary Algorithms and Applications
- Metaheuristic Optimization Algorithms Research
- Text and Document Classification Technologies
- Topic Modeling
- Computer Science Applications top 10%
Papers in
-
- Evolutionary Algorithms and Applications 22
- Metaheuristic Optimization Algorithms Research 18
- Sentiment Analysis and Opinion Mining 10
- Advanced Text Analysis Techniques 7
- Neural Networks and Applications 6
- Hate Speech and Cyberbullying Detection 5
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- Stock Market Forecasting Methods 7
- Co-authors
- Eric S. Téllez (30 shared papers)Sabino Miranda‐Jiménez (21 shared papers)Hugo Jair Escalante (10 shared papers)Juan J. Flores (7 shared papers)Daniela Moctezuma (21 shared papers)Héctor Rodríguez (2 shared papers)Riccardo Poli (6 shared papers)Ramón Zataraín Cabada (1 shared paper)
- Journals
- Renewable Energy (2 papers)Natural Computing (2 papers)Expert Systems with Applications (2 papers)Knowledge-Based Systems (1 paper)IEEE Access (1 paper)
- Partner nations
- MexicoSpainUnited Kingdom
In The Last Decade
Mario Graff
62 papers receiving 609 citations
Peers
Comparison fields: 5 of 113
- Artificial Intelligence 411
- Computer Science Applications 31
- Management Science and Operations Research 71
- Information Systems 82
- Signal Processing 35
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 65 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 71 | |
| 2 | 2012 | 62 | |
| 3 | 2015 | 49 | |
| 4 | 2017 | 43 | |
| 5 | 2017 | 30 | |
| 6 | 2015 | 22 | |
| 7 | 2010 | 17 | |
| 8 | 2016 | 17 | |
| 9 | 2013 | 17 | |
| 10 | 2014 | 17 | |
| 11 | 2013 | 16 | |
| 12 | 2009 | 16 | |
| 13 | 2015 | 15 | |
| 14 | 2014 | 15 | |
| 15 | 2009 | 14 | |
| 16 | 2016 | 14 | |
| 17 | 2018 | 13 | |
| 18 | Overview of TASS 2019: One More Further for the Global Spanish Sentiment Analysis Corpus. | 2019 | 12 |
| 19 | 2015 | 12 | |
| 20 | 2013 | 11 |
About Mario Graff
Mario Graff is a scholar working on Artificial Intelligence, Management Science and Operations Research, Electrical and Electronic Engineering, Information Systems and Computer Vision and Pattern Recognition, having authored 65 papers that have together received 638 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (22 papers), Metaheuristic Optimization Algorithms Research (18 papers), Sentiment Analysis and Opinion Mining (10 papers), Stock Market Forecasting Methods (7 papers), Advanced Text Analysis Techniques (7 papers), Neural Networks and Applications (6 papers), Energy Load and Power Forecasting (6 papers) and Hate Speech and Cyberbullying Detection (5 papers). The work is most often cited by research in Artificial Intelligence (411 citations), Computer Science Applications (31 citations), Management Science and Operations Research (71 citations), Information Systems (82 citations) and Signal Processing (35 citations). Mario Graff has collaborated with scholars based in Mexico, Spain and United Kingdom. Frequent co-authors include Eric S. Téllez, Sabino Miranda‐Jiménez, Hugo Jair Escalante, Juan J. Flores, Daniela Moctezuma, Héctor Rodríguez, Riccardo Poli, Ramón Zataraín Cabada, María Lucía Barrón Estrada and Raúl Oramas Bustillos. Their work appears in journals such as Renewable Energy, Natural Computing, Expert Systems with Applications, Knowledge-Based Systems and IEEE Access.
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.