Diego Seco

445 total citations
31 papers, 128 citations indexed

About

Diego Seco is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Diego Seco has authored 31 papers receiving a total of 128 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Signal Processing, 15 papers in Artificial Intelligence and 14 papers in Computer Networks and Communications. Recurrent topics in Diego Seco's work include Data Management and Algorithms (15 papers), Algorithms and Data Compression (14 papers) and Geographic Information Systems Studies (6 papers). Diego Seco is often cited by papers focused on Data Management and Algorithms (15 papers), Algorithms and Data Compression (14 papers) and Geographic Information Systems Studies (6 papers). Diego Seco collaborates with scholars based in Chile, Spain and Canada. Diego Seco's co-authors include Miguel R. Luaces, Nieves R. Brisaboa, M. Andrea Rodríguez, Zheng Li, Gonzalo Navarro, Leo Ferres, Antonio Fariña, José Ignacio Abreu, José R. Paramá and Óscar Pedreira and has published in prestigious journals such as Communications of the ACM, IEEE Access and Sensors.

In The Last Decade

Diego Seco

27 papers receiving 121 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Diego Seco Chile 7 61 52 50 33 22 31 128
Philippe Rigaux France 9 68 1.1× 162 3.1× 120 2.4× 76 2.3× 57 2.6× 32 260
Octavian Procopiuc United States 5 77 1.3× 127 2.4× 91 1.8× 54 1.6× 16 0.7× 9 215
Nora Susana Reyes Argentina 8 79 1.3× 158 3.0× 61 1.2× 32 1.0× 12 0.5× 40 192
Sukho Lee South Korea 6 86 1.4× 190 3.7× 173 3.5× 85 2.6× 36 1.6× 16 252
Cristina Dutra de Aguiar Ciferri Brazil 9 40 0.7× 134 2.6× 132 2.6× 94 2.8× 22 1.0× 56 213
Thomas Ohler Switzerland 3 73 1.2× 149 2.9× 186 3.7× 54 1.6× 16 0.7× 4 238
Michael Rys United States 9 169 2.8× 166 3.2× 269 5.4× 82 2.5× 18 0.8× 28 319
Liping Peng United States 8 112 1.8× 98 1.9× 116 2.3× 70 2.1× 7 0.3× 13 224
Juncheng Yang United States 10 111 1.8× 70 1.3× 203 4.1× 117 3.5× 14 0.6× 27 325
Ahmed M. Aly United States 10 56 0.9× 214 4.1× 196 3.9× 82 2.5× 48 2.2× 23 278

Countries citing papers authored by Diego Seco

Since Specialization
Citations

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

Fields of papers citing papers by Diego Seco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Diego Seco

This figure shows the co-authorship network connecting the top 25 collaborators of Diego Seco. A scholar is included among the top collaborators of Diego Seco 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 Diego Seco. Diego Seco is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cabrera-Vives, G., et al.. (2023). A Novel Two-Phase Approach to Forest Harvesting Optimization Using Cable Logging. Forests. 14(11). 2133–2133. 1 indexed citations
2.
López-Vázquez, Carlos, et al.. (2022). Building a Gold Standard Dataset to Identify Articles About Geographic Information Science. IEEE Access. 10. 19926–19936. 1 indexed citations
3.
Navarro, Gonzalo, et al.. (2022). Navigating planar topologies in near-optimal space and time. Computational Geometry. 109. 101922–101922. 1 indexed citations
4.
Seco, Diego, et al.. (2022). Speeding up compact planar graphs by using shallower trees. 282–291.
5.
Gagie, Travis, et al.. (2022). Faster compressed quadtrees. Journal of Computer and System Sciences. 131. 86–104. 1 indexed citations
6.
Abreu, José Ignacio, et al.. (2021). Boosting Perturbation-Based Iterative Algorithms to Compute the Median String. IEEE Access. 9. 169299–169308.
7.
Paramá, José R., et al.. (2021). Space-efficient representations of raster time series. Information Sciences. 566. 300–325. 2 indexed citations
8.
Seco, Diego, et al.. (2020). Boosting Point-of-Interest Recommendation with Multigranular Time Representations. JUCS - Journal of Universal Computer Science. 22. 1148–1174. 1 indexed citations
9.
Martínez‐Prieto, Miguel A., et al.. (2020). cBiK: A Space-Efficient Data Structure for Spatial Keyword Queries. IEEE Access. 8. 98827–98846. 2 indexed citations
10.
Arroyuelo, Diego, et al.. (2020). Three success stories about compact data structures. Communications of the ACM. 63(11). 64–65.
11.
Rodríguez, M. Andrea, et al.. (2019). Covering a Set of Points with k Bounding Boxes. 1–6. 1 indexed citations
12.
Li, Zheng, et al.. (2019). Microservice-Oriented Platform for Internet of Big Data Analytics: A Proof of Concept. Sensors. 19(5). 1134–1134. 13 indexed citations
13.
Abreu, José Ignacio, et al.. (2019). Assessing the best edit in perturbation-based iterative refinement algorithms to compute the median string. Pattern Recognition Letters. 120. 104–111. 5 indexed citations
14.
Ferres, Leo, et al.. (2016). Parallel construction of wavelet trees on multicore architectures. Knowledge and Information Systems. 51(3). 1043–1066. 6 indexed citations
15.
Gagie, Travis, et al.. (2015). Faster Compressed Quadtrees. 93–102. 4 indexed citations
16.
Claude, Francisco, Patrick K. Nicholson, & Diego Seco. (2013). On the compression of search trees. Information Processing & Management. 50(2). 272–283. 2 indexed citations
17.
Brisaboa, Nieves R., Miguel R. Luaces, M. Andrea Rodríguez, & Diego Seco. (2013). An inconsistency measure of spatial data sets with respect to topological constraints. International Journal of Geographical Information Systems. 28(1). 56–82. 13 indexed citations
18.
Claude, Francisco, Patrick K. Nicholson, & Diego Seco. (2012). Differentially Encoded Search Trees. 357–366. 2 indexed citations
19.
Brisaboa, Nieves R., et al.. (2010). Exploiting geographic references of documents in a geographical information retrieval system using an ontology-based index. GeoInformatica. 14(3). 307–331. 15 indexed citations
20.

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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