Luis Martínez (ORCID: 0000-0003-4245-8813): h-index, Total Citations, and Citation Map
Luis Martínez (ORCID: 0000-0003-4245-8813)'s h-index is 87 (341 i10-index, 36,183+ total citations across 2+ publications) according to Google Scholar as of May 2026. Luis Martínez (ORCID: 0000-0003-4245-8813) is affiliated with Professor of Computer Science, University of Jaén.
Luis Martínez (ORCID: 0000-0003-4245-8813) is a researcher affiliated with Professor of Computer Science, University of Jaén, specializing in Fuzzy decision making, Computing with words, Recommender Systems. Their work has been cited 36,183 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Luis Martínez (ORCID: 0000-0003-4245-8813)'s Citation Metrics
Bibliometric impact based on 2 indexed publications.
- H-Index
- 87
- i10-Index
- 341
- Total Citations
- 36,183
- Citing Countries
- 8
As of May 2026.
Luis Martínez (ORCID: 0000-0003-4245-8813) has an h-index of 87 and 36,183 total citations across 2 publications, with research cited by institutions in 8 countries.
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Top Cited Works
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A 2-Tuple Fuzzy Linguistic Representation Model for Computing with Words
20023,711
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Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
The researcher developed a linguistic 2-tuple model to handle multigranular hierarchical contexts in multi-expert decision-making, establishing a foundational framework for complex qualitative data processing.
The researcher developed a 2-tuple fuzzy linguistic representation model for computing with words, establishing a foundational framework for handling linguistic information in fuzzy systems.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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