Alvaro Graves

29 total papers · 668 total citations
20 papers, 401 citations indexed

About

Alvaro Graves is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Management Science and Operations Research. According to data from OpenAlex, Alvaro Graves has authored 20 papers receiving a total of 401 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 7 papers in Management Science and Operations Research. Recurrent topics in Alvaro Graves's work include Semantic Web and Ontologies (10 papers), Data Quality and Management (7 papers) and Data Visualization and Analytics (7 papers). Alvaro Graves is often cited by papers focused on Semantic Web and Ontologies (10 papers), Data Quality and Management (7 papers) and Data Visualization and Analytics (7 papers). Alvaro Graves collaborates with scholars based in United States, Chile and United Kingdom. Alvaro Graves's co-authors include James Hendler, Dominic DiFranzo, Deborah L. McGuinness, James Michaelis, Li Ding, John Erickson, Jin Zheng, Timothy Lebo, Gregory Todd Williams and Xian Li and has published in prestigious journals such as Future Generation Computer Systems, Journal of Web Semantics and Information Polity.

In The Last Decade

Alvaro Graves

20 papers receiving 377 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Alvaro Graves 228 167 128 101 54 20 401
Bernadette Farias Lóscio 108 0.5× 146 0.9× 57 0.4× 119 1.2× 58 1.1× 44 348
Syed Waqar Jaffry 265 1.2× 59 0.4× 25 0.2× 80 0.8× 42 0.8× 34 445
Shirlee-ann Knight 78 0.3× 185 1.1× 24 0.2× 151 1.5× 23 0.4× 17 406
Boris Villazón-Terrazas 275 1.2× 62 0.4× 23 0.2× 138 1.4× 68 1.3× 41 355
Pritheega Magalingam 190 0.8× 33 0.2× 21 0.2× 139 1.4× 71 1.3× 36 422
Victor Rodrı́guez-Doncel 184 0.8× 22 0.1× 43 0.3× 113 1.1× 17 0.3× 49 347
Benoît Otjacques 88 0.4× 21 0.1× 66 0.5× 69 0.7× 24 0.4× 36 442
Symeon Symeonidis 199 0.9× 47 0.3× 20 0.2× 69 0.7× 10 0.2× 24 380
Mirko Cesarini 140 0.6× 48 0.3× 10 0.1× 145 1.4× 26 0.5× 39 394
Fouad Zablith 252 1.1× 26 0.2× 19 0.1× 116 1.1× 32 0.6× 22 357

Countries citing papers authored by Alvaro Graves

Since Specialization
Citations

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

Fields of papers citing papers by Alvaro Graves

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alvaro Graves

This figure shows the co-authorship network connecting the top 25 collaborators of Alvaro Graves. A scholar is included among the top collaborators of Alvaro Graves based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Alvaro Graves. Alvaro Graves is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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