Sérgio Canuto

626 total citations
25 papers, 424 citations indexed

About

Sérgio Canuto is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Sérgio Canuto has authored 25 papers receiving a total of 424 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Information Systems. Recurrent topics in Sérgio Canuto's work include Text and Document Classification Technologies (14 papers), Topic Modeling (13 papers) and Machine Learning and Data Classification (6 papers). Sérgio Canuto is often cited by papers focused on Text and Document Classification Technologies (14 papers), Topic Modeling (13 papers) and Machine Learning and Data Classification (6 papers). Sérgio Canuto collaborates with scholars based in Brazil, Slovakia and Portugal. Sérgio Canuto's co-authors include Marcos André Gonçalves, Thierson Couto Rosa, Leonardo Rocha, Felipe Viegas, Fabrí­cio Benevenuto, Christian Gomes, Wellington S. Martins, Thiago Salles, Jussara M. Almeida and Mirella M. Moro and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Information Sciences.

In The Last Decade

Sérgio Canuto

24 papers receiving 407 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sérgio Canuto Brazil 13 333 114 45 37 20 25 424
Jarosław Protasiewicz Canada 7 213 0.6× 110 1.0× 34 0.8× 26 0.7× 7 0.3× 14 311
Jagdev Bhogal United Kingdom 7 251 0.8× 176 1.5× 35 0.8× 28 0.8× 7 0.3× 18 376
Zhiyang Teng China 12 517 1.6× 61 0.5× 75 1.7× 79 2.1× 6 0.3× 25 640
Faezeh Ensan Canada 13 291 0.9× 230 2.0× 28 0.6× 33 0.9× 5 0.3× 44 373
Yogesh Kumar Meena India 13 293 0.9× 124 1.1× 70 1.6× 17 0.5× 8 0.4× 56 468
Marcin Mirończuk Poland 6 182 0.5× 69 0.6× 25 0.6× 23 0.6× 6 0.3× 22 260
Noureddine En-Nahnahi Morocco 14 409 1.2× 82 0.7× 67 1.5× 16 0.4× 5 0.3× 40 532
Gregor Heinrich Germany 3 305 0.9× 158 1.4× 69 1.5× 15 0.4× 32 1.6× 6 472
Henda Hajjami Ben Ghézala Tunisia 9 178 0.5× 122 1.1× 13 0.3× 17 0.5× 7 0.3× 47 305

Countries citing papers authored by Sérgio Canuto

Since Specialization
Citations

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

Fields of papers citing papers by Sérgio Canuto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sérgio Canuto

This figure shows the co-authorship network connecting the top 25 collaborators of Sérgio Canuto. A scholar is included among the top collaborators of Sérgio Canuto 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 Sérgio Canuto. Sérgio Canuto 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.
Viegas, Felipe, et al.. (2024). Pipelining Semantic Expansion and Noise Filtering for Sentiment Analysis of Short Documents – CluSent Method. SHILAP Revista de lepidopterología. 15(1). 561–575.
2.
3.
Etges, Ana Paula Beck da Silva, Ana Cláudia de Souza, Felipe Viegas, et al.. (2021). Stroke Outcome Measurements From Electronic Medical Records: Cross-sectional Study on the Effectiveness of Neural and Nonneural Classifiers. JMIR Medical Informatics. 9(11). e29120–e29120. 8 indexed citations
4.
Gomes, Christian, Marcos André Gonçalves, Leonardo Rocha, & Sérgio Canuto. (2021). On the Cost-Effectiveness of Stacking of Neural and Non-Neural Methods for Text Classification: Scenarios and Performance Prediction. 4003–4014. 5 indexed citations
5.
Mangaravite, Vítor, Christian Gomes, Sérgio Canuto, et al.. (2021). On the cost-effectiveness of neural and non-neural approaches and representations for text classification: A comprehensive comparative study. Information Processing & Management. 58(3). 102481–102481. 56 indexed citations
6.
Viegas, Felipe, Mário S. Alvim, Sérgio Canuto, et al.. (2020). Exploiting semantic relationships for unsupervised expansion of sentiment lexicons. Information Systems. 94. 101606–101606. 21 indexed citations
7.
Belém, Fabiano, et al.. (2019). Image Aesthetics and its Effects on Product Clicks in E-Commerce Search.. International ACM SIGIR Conference on Research and Development in Information Retrieval. 4 indexed citations
8.
Gonçalves, Marcos André, et al.. (2019). Quality assessment of collaboratively-created web content with no manual intervention based on soft multi-view generation. Expert Systems with Applications. 132. 226–238. 1 indexed citations
9.
Canuto, Sérgio, et al.. (2019). Risk-Sensitive Learning to Rank with Evolutionary Multi-Objective Feature Selection. ACM Transactions on Information Systems. 37(2). 1–34. 16 indexed citations
10.
Canuto, Sérgio, Thiago Salles, Thierson Couto Rosa, & Marcos André Gonçalves. (2019). Similarity-Based Synthetic Document Representations for Meta-Feature Generation in Text Classification. 355–364. 13 indexed citations
11.
Viegas, Felipe, Sérgio Canuto, Christian Gomes, et al.. (2019). CluWords. 753–761. 34 indexed citations
12.
Canuto, Sérgio, et al.. (2018). A pragmatic approach to hierarchical categorization of research expertise in the presence of scarce information. International Journal on Digital Libraries. 21(1). 61–73. 9 indexed citations
13.
Canuto, Sérgio, et al.. (2018). A Thorough Evaluation of Distance-Based Meta-Features for Automated Text Classification. IEEE Transactions on Knowledge and Data Engineering. 30(12). 2242–2256. 23 indexed citations
14.
Viegas, Felipe, Christian Gomes, Sérgio Canuto, et al.. (2018). Semantically-Enhanced Topic Modeling. 893–902. 9 indexed citations
15.
Canuto, Sérgio, et al.. (2016). Incorporating Risk-Sensitiveness into Feature Selection for Learning to Rank. 257–266. 11 indexed citations
16.
Canuto, Sérgio, et al.. (2016). Ranked batch-mode active learning. Information Sciences. 379. 313–337. 45 indexed citations
17.
Canuto, Sérgio, Marcos André Gonçalves, & Fabrí­cio Benevenuto. (2016). Exploiting New Sentiment-Based Meta-level Features for Effective Sentiment Analysis. 53–62. 47 indexed citations
18.
Galante, Renata, et al.. (2016). A practical and effective sampling selection strategy for large scale deduplication. 1518–1519. 4 indexed citations
19.
Canuto, Sérgio, et al.. (2013). UDRB: Uma Nova Heurística Eficaz para Deduplicação de Referências Bibliográficas.. 1 indexed citations
20.
Canuto, Sérgio, Fabiano Belém, Jussara M. Almeida, & Marcos André Gonçalves. (2013). A Comparative Study of Learning-to-Rank Techniques for Tag Recommendation. Cadernos de Linguística e Teoria da Literatura (Universidade Federal de Minas Gerais). 4(3). 453–468. 17 indexed citations

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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