Daniel Gómez

154 papers receiving 2.4k citations

Peers

Daniel Gómez
Comparison fields: 5 of 161
  • Management Science and Operations Research 928
  • Computational Theory and Mathematics 570
  • Statistics and Probability 239
  • Statistical and Nonlinear Physics 322
  • Artificial Intelligence 649
Replace Naeem Jan with:
Naeem Jan Canada
Wray Buntine Australia
Ying Hu China
Fred S. Roberts United States
Alan J. Mayne Australia
Moritz Hardt United States
Yoshiteru Nakamori Japan
Adam Tauman Kalai United States
David Rı́os Insua Spain
Malik Magdon‐Ismail United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Gómez

Since Specialization
Citations

This map shows the geographic impact of Daniel Gómez'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 Daniel Gómez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Gómez more than expected).

Fields of papers citing papers by Daniel Gómez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Gómez. 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 Daniel Gómez. The network helps show where Daniel Gómez may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Gómez, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Gómez Line = papers co-authored together Daniel Gómez links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 165 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008387
2 2003160
3 2007114
4 2014113
5 201893
6
Informe nacional de Competitividad 2013-2014
201689
7 201686
8 200175
9 201771
10 201266
11
A discussion on aggregation operators.
200455
12 200752
13 201548
14 201741
15 200238
16 200537
17 201534
18 199931
19 201329
20 200628

About Daniel Gómez

Daniel Gómez is a scholar working on Management Science and Operations Research, Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 165 papers that have together received 2.5k indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (50 papers), Rough Sets and Fuzzy Logic (28 papers), Complex Network Analysis Techniques (23 papers), Fuzzy Systems and Optimization (22 papers), Image Retrieval and Classification Techniques (20 papers), Medical Image Segmentation Techniques (19 papers), Fuzzy Logic and Control Systems (15 papers) and Advanced Algebra and Logic (13 papers). The work is most often cited by research in Management Science and Operations Research (928 citations), Computational Theory and Mathematics (570 citations), Statistics and Probability (239 citations), Statistical and Nonlinear Physics (322 citations) and Artificial Intelligence (649 citations). Daniel Gómez has collaborated with scholars based in Spain, Colombia and United States. Frequent co-authors include Javier Montero, Juan Tejada, Javier Castro, J. Tinguaro Rodríguez, Humberto Bustince, Javier Yáñez, Ángel Alegría, Juan Colmenero, Enrique González–Arangüena and Conrado Manuel. Their work appears in journals such as Fuzzy Sets and Systems, International Journal of Computational Intelligence Systems, Information Sciences, European Journal of Operational Research and Computers & Operations Research.

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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