Daniel Sánchez

119 papers receiving 1.7k citations

Peers

Daniel Sánchez
Comparison fields: 5 of 118
  • Computational Theory and Mathematics 704
  • Signal Processing 429
  • Information Systems 776
  • Artificial Intelligence 1.0k
  • Management Science and Operations Research 236
Replace Umberto Straccia with:
Umberto Straccia Italy
Nick Cercone Canada
Bay Vo Vietnam
Alberto Cano United States
Eui-Hong Han United States
Mustafa Mat Deris Malaysia
Nicolás Marı́n Spain
Howard J. Hamilton Canada
Zongmin Ma China
Mohammad Karim Sohrabi Iran
Daniel Sánchez relative to Umberto Straccia Italy Umberto Straccia's profile →
Citations per field
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Umberto Straccia · 1×
Citations per year

Countries citing papers authored by Daniel Sánchez

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Sánchez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Sánchez, 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 Sánchez Line = papers co-authored together Daniel Sánchez links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 123 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003211
2 2008173
3 2000110
4 2002106
5 201376
6
A Fuzzy Approach to the Linguistic Summarization of Time Series.
201148
7 201548
8 200147
9 201145
10 200343
11 200735
12 200233
13 201831
14 200331
15 200428
16 201128
17 200327
18 201127
19 200826
20 201626

About Daniel Sánchez

Daniel Sánchez is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Information Systems, Signal Processing and Computer Vision and Pattern Recognition, having authored 123 papers that have together received 1.9k indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (58 papers), Data Mining Algorithms and Applications (33 papers), Data Management and Algorithms (30 papers), Multi-Criteria Decision Making (19 papers), Semantic Web and Ontologies (17 papers), Image Retrieval and Classification Techniques (17 papers), Fuzzy Logic and Control Systems (13 papers) and Natural Language Processing Techniques (12 papers). The work is most often cited by research in Computational Theory and Mathematics (704 citations), Signal Processing (429 citations), Information Systems (776 citations), Artificial Intelligence (1.0k citations) and Management Science and Operations Research (236 citations). Daniel Sánchez has collaborated with scholars based in Spain, United States and Azerbaijan. Frequent co-authors include M.A. Vila, Nicolás Marı́n, Miguel Delgado‐Rodríguez, José-Marı́a Serrano, M. Dolores Ruiz, J. Chamorro-Martı́nez, Marı́a J. Martı́n-Bautista, Fernando Berzal, Ignacio J. Blanco and Miguel Delgado. Their work appears in journals such as Fuzzy Sets and Systems, International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, IEEE Transactions on Fuzzy Systems, Information Sciences and Expert Systems with Applications.

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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