Nele Verbiest

932 total citations
18 papers, 503 citations indexed

About

Nele Verbiest is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Information Systems. According to data from OpenAlex, Nele Verbiest has authored 18 papers receiving a total of 503 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computational Theory and Mathematics, 11 papers in Artificial Intelligence and 9 papers in Information Systems. Recurrent topics in Nele Verbiest's work include Rough Sets and Fuzzy Logic (10 papers), Data Mining Algorithms and Applications (8 papers) and Machine Learning and Data Classification (5 papers). Nele Verbiest is often cited by papers focused on Rough Sets and Fuzzy Logic (10 papers), Data Mining Algorithms and Applications (8 papers) and Machine Learning and Data Classification (5 papers). Nele Verbiest collaborates with scholars based in Belgium, Spain and United Kingdom. Nele Verbiest's co-authors include Chris Cornelis, Francisco Herrera, Enislay Ramentol, Lluı́s Godo, Lynn D’eer, Patricia Victor, Sarah Vluymans, Jesús Medina, Salvador García and Yailé Caballero Mota and has published in prestigious journals such as Pattern Recognition, IEEE Transactions on Fuzzy Systems and Fuzzy Sets and Systems.

In The Last Decade

Nele Verbiest

17 papers receiving 484 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nele Verbiest Belgium 11 329 227 137 81 50 18 503
Janice R. Boughton Australia 4 429 1.3× 66 0.3× 135 1.0× 59 0.7× 54 1.1× 5 574
Jingnian Chen China 5 364 1.1× 46 0.2× 189 1.4× 23 0.3× 95 1.9× 16 526
Peter Butka Slovakia 10 165 0.5× 125 0.6× 117 0.9× 49 0.6× 18 0.4× 46 385
Yu Wu China 13 181 0.6× 78 0.3× 189 1.4× 27 0.3× 50 1.0× 63 519
Chenyang Bu China 12 319 1.0× 125 0.6× 60 0.4× 60 0.7× 55 1.1× 54 436
Rajen B. Bhatt India 9 205 0.6× 259 1.1× 179 1.3× 80 1.0× 62 1.2× 24 424
Fardin Akhlaghian Iran 9 294 0.9× 39 0.2× 206 1.5× 37 0.5× 248 5.0× 15 574
Sarah Vluymans Belgium 12 328 1.0× 165 0.7× 95 0.7× 62 0.8× 83 1.7× 16 467
Ernestas Filatovas Lithuania 11 153 0.5× 119 0.5× 109 0.8× 38 0.5× 34 0.7× 36 366

Countries citing papers authored by Nele Verbiest

Since Specialization
Citations

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

Fields of papers citing papers by Nele Verbiest

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nele Verbiest

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

All Works

18 of 18 papers shown
1.
Verbiest, Nele, Sarah Vluymans, Chris Cornelis, Nicolás García‐Pedrajas, & Yvan Saeys. (2016). Improving nearest neighbor classification using Ensembles of Evolutionary Generated Prototype Subsets. Applied Soft Computing. 44. 75–88. 11 indexed citations
2.
Verbiest, Nele, Joaquín Derrac, Chris Cornelis, Salvador García, & Francisco Herrera. (2015). Evolutionary wrapper approaches for training set selection as preprocessing mechanism for support vector machines: Experimental evaluation and support vector analysis. Applied Soft Computing. 38. 10–22. 43 indexed citations
3.
D’eer, Lynn, Nele Verbiest, Chris Cornelis, & Lluı́s Godo. (2014). A comprehensive study of implicator–conjunctor-based and noise-tolerant fuzzy rough sets: Definitions, properties and robustness analysis. Fuzzy Sets and Systems. 275. 1–38. 85 indexed citations
4.
Verbiest, Nele, Enislay Ramentol, Chris Cornelis, & Francisco Herrera. (2014). Preprocessing noisy imbalanced datasets using SMOTE enhanced with fuzzy rough prototype selection. Applied Soft Computing. 22. 511–517. 76 indexed citations
5.
Vluymans, Sarah, Nele Verbiest, Chris Cornelis, & Yvan Saeys. (2014). Instance Selection for Imbalanced Data. Ghent University Academic Bibliography (Ghent University). 9–9. 2 indexed citations
6.
Srinivasan, Rajagopalan, et al.. (2014). Computing fuzzy rough approximations in large scale information systems. Ghent University Academic Bibliography (Ghent University). 9–16. 7 indexed citations
7.
Ramentol, Enislay, Sarah Vluymans, Nele Verbiest, et al.. (2014). IFROWANN: Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classification. IEEE Transactions on Fuzzy Systems. 23(5). 1622–1637. 83 indexed citations
8.
Cornelis, Chris, Jesús Medina, & Nele Verbiest. (2013). Multi-adjoint fuzzy rough sets: Definition, properties and attribute selection. International Journal of Approximate Reasoning. 55(1). 412–426. 41 indexed citations
9.
Zolfaghar, Kiyana, et al.. (2013). Risk-O-Meter. Ghent University Academic Bibliography (Ghent University). 1518–1521. 10 indexed citations
10.
Verbiest, Nele, Chris Cornelis, & Richard Jensen. (2013). Quality, frequency and similarity based fuzzy nearest neighbor classification. Ghent University Academic Bibliography (Ghent University). 1–8. 4 indexed citations
11.
Verbiest, Nele, Chris Cornelis, & Francisco Herrera. (2013). FRPS: A Fuzzy Rough Prototype Selection method. Pattern Recognition. 46(10). 2770–2782. 41 indexed citations
12.
Victor, Patricia, Nele Verbiest, Chris Cornelis, & Martine De Cock. (2013). Enhancing the trust-based recommendation process with explicit distrust. ACM Transactions on the Web. 7(2). 1–19. 33 indexed citations
13.
Verbiest, Nele, Chris Cornelis, Patricia Victor, & Enrique Herrera‐Viedma. (2012). Trust and distrust aggregation enhanced with path length incorporation. Fuzzy Sets and Systems. 202. 61–74. 30 indexed citations
14.
Verbiest, Nele, Chris Cornelis, & Francisco Herrera. (2012). Selección de prototipos basada en conjuntos rugosos difusos. Ghent University Academic Bibliography (Ghent University). 638–643.
15.
Verbiest, Nele, et al.. (2012). On the use of evolutionary feature selection for improving fuzzy rough set based prototype selection. Soft Computing. 17(2). 223–238. 23 indexed citations
16.
Verbiest, Nele, Chris Cornelis, & Richard Jensen. (2012). Fuzzy rough positive region based nearest neighbour classification. Aberystwyth Research portal (Aberystwyth University). 1–7. 12 indexed citations
17.
Cornelis, Chris, Jesús Medina, & Nele Verbiest. (2011). Multi-Adjoint Fuzzy Rough Sets. Ghent University Academic Bibliography (Ghent University). 1 indexed citations
18.
Verbiest, Nele, Chris Cornelis, & Yvan Saeys. (2009). Valued constraint satisfaction problems applied to functional harmony. European Society for Fuzzy Logic and Technology Conference. 136(9). 925–930. 1 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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