Geert De Soete

2.8k total citations
56 papers, 1.8k citations indexed

About

Geert De Soete is a scholar working on Signal Processing, Artificial Intelligence and Food Science. According to data from OpenAlex, Geert De Soete has authored 56 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Signal Processing, 8 papers in Artificial Intelligence and 8 papers in Food Science. Recurrent topics in Geert De Soete's work include Sensory Analysis and Statistical Methods (8 papers), Data Management and Algorithms (6 papers) and Consumer Market Behavior and Pricing (6 papers). Geert De Soete is often cited by papers focused on Sensory Analysis and Statistical Methods (8 papers), Data Management and Algorithms (6 papers) and Consumer Market Behavior and Pricing (6 papers). Geert De Soete collaborates with scholars based in Belgium, United States and France. Geert De Soete's co-authors include Suzanne Winsberg, J. Douglas Carroll, Sophie Donnadieu, Stephen McAdams, Wayne S. DeSarbo, Constantin Jannes, Guy Vingerhoets, Engelien Lannoo, Francis Colardyn and Tom Vandekerckhove and has published in prestigious journals such as PLoS ONE, American Psychologist and Journal of Psychosomatic Research.

In The Last Decade

Geert De Soete

52 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Geert De Soete Belgium	20	368	350	305	219	216	56	1.8k
R. N. Curnow United Kingdom	25	456 1.2×	71 0.2×	218 0.7×	112 0.5×	175 0.8×	106	3.3k
Mark C. K. Yang United States	24	198 0.5×	71 0.2×	153 0.5×	44 0.2×	206 1.0×	60	1.8k
Diego H. Milone Argentina	26	477 1.3×	355 1.0×	107 0.4×	269 1.2×	57 0.3×	129	2.3k
R. Clifford Blair United States	23	135 0.4×	76 0.2×	1.3k 4.3×	66 0.3×	34 0.2×	60	3.3k
James P. Egan United States	14	119 0.3×	192 0.5×	799 2.6×	142 0.6×	52 0.2×	36	2.2k
Forrest Sheng Bao United States	23	248 0.7×	211 0.6×	662 2.2×	171 0.8×	162 0.8×	65	2.6k
Amir Bashan Israel	19	489 1.3×	71 0.2×	412 1.4×	23 0.1×	112 0.5×	38	2.5k
Romain Vuillemot France	10	628 1.7×	94 0.3×	37 0.1×	465 2.1×	133 0.6×	20	1.9k
Stephanie Seneff United States	36	315 0.9×	989 2.8×	212 0.7×	287 1.3×	55 0.3×	253	5.7k
Thaddeus Tarpey United States	19	70 0.2×	73 0.2×	109 0.4×	89 0.4×	27 0.1×	78	1.1k

Countries citing papers authored by Geert De Soete

Since Specialization

Citations

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

Fields of papers citing papers by Geert De Soete

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Geert De Soete. 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 Geert De Soete. The network helps show where Geert De Soete may publish in the future.

Co-authorship network of co-authors of Geert De Soete

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

All Works

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20 of 20 papers shown

Lannoo, Engelien, C. De Deyne, Francis Colardyn, Geert De Soete, & Constantin Jannes. (1997). Personality change following head injury: Assessment with the neo five-factor inventory. Journal of Psychosomatic Research. 43(5). 505–511. 23 indexed citations

Vingerhoets, Guy, Constantin Jannes, Geert De Soete, & Guido Van Nooten. (1996). Prospective Evaluation of Verbal Memory Performance after Cardiopulmonary Bypass Surgery. Journal of Clinical and Experimental Neuropsychology. 18(2). 187–196. 20 indexed citations

McAdams, Stephen, et al.. (1995). Perceptual scaling of synthesized musical timbres: Common dimensions, specificities, and latent subject classes. Psychological Research. 58(3). 177–192. 369 indexed citations

Soete, Geert De & Suzanne Winsberg. (1993). A latent class vector model for preference ratings. Journal of Classification. 10(2). 195–218. 21 indexed citations

Soete, Geert De & Suzanne Winsberg. (1993). A Thurstonian Pairwise Choice Model with Univariate and Multivariate Spline Transformations. Psychometrika. 58(2). 233–256. 14 indexed citations

Soete, Geert De & Willem J. Heiser. (1993). A Latent Class Unfolding Model for Analyzing Single Stimulus Preference Ratings. Psychometrika. 58(4). 545–565. 25 indexed citations

Soete, Geert De. (1992). 3-way scaling and clustering: Arabie, P, Carroll, JD, Desarbo, WS. Ghent University Academic Bibliography (Ghent University). 1 indexed citations

Vandierendonck, André, et al.. (1990). Some effects of menu characteristics and user personality on performance with menu-driven interfaces. Behaviour and Information Technology. 9(1). 17–29. 7 indexed citations

Soete, Geert De & J. Douglas Carroll. (1989). Ultrametric tree representations of three-way three-mode data. 415–426. 1 indexed citations

10.

Carroll, J. Douglas, Geert De Soete, & Sandra Pruzansky. (1989). Fitting of the Latent Class model via iteratively reweighted least squares CANDECOMP with nonnegativity constraints. 463–472. 13 indexed citations

11.

Soete, Geert De, et al.. (1989). Free-response self-description as a predictor of success and failure in adolescent exchange students. International Journal of Intercultural Relations. 13(1). 73–91. 6 indexed citations

12.

DeSarbo, Wayne S., Geert De Soete, J. Douglas Carroll, & Venkatram Ramaswamy. (1988). A New Stochastic Ultrametric Tree Unfolding Methodology for Assessing Competitive Market Structure and Deriving Market Segments. SSRN Electronic Journal.

13.

Carroll, J. Douglas, Wayne S. DeSarbo, & Geert De Soete. (1987). Stochastic Tree Unfolding (STUN) Models. SSRN Electronic Journal. 3 indexed citations

14.

DeSarbo, Wayne S., Geert De Soete, & Kamel Jedidi. (1987). Probabilistic Multidimensional Scaling Models for Analyzing Consumer Choice. SSRN Electronic Journal. 2 indexed citations

15.

Soete, Geert De, J. Douglas Carroll, & Wayne S. DeSarbo. (1987). Least squares algorithms for constructing constrained ultrametric and additive tree representations of symmetric proximity data. Journal of Classification. 4(2). 155–173. 14 indexed citations

16.

Soete, Geert De, J. Douglas Carroll, & Wayne S. DeSarbo. (1986). The Wandering Ideal Point Model: A Probabilistic Multidimensional Unfolding Model for Paired Comparisons Data. SSRN Electronic Journal. 3 indexed citations

17.

Soete, Geert De, J. Douglas Carroll, & Wayne S. DeSarbo. (1986). Alternating Least Squares Optimal Variable Weighting Algorithms for Ultrametric and Additive Tree Representations. SSRN Electronic Journal. 1 indexed citations

18.

DeSarbo, Wayne S., Richard L. Oliver, & Geert De Soete. (1986). A Probabilistic Multidimensional Scaling Vector Model. SSRN Electronic Journal. 1 indexed citations

19.

Soete, Geert De. (1984). On the Validity of Luce’s Similarity Choice Model for Confusion Data. Psychologica Belgica. 24(1). 83–83. 1 indexed citations

20.

Soete, Geert De. (1984). Computer programs for fitting ultrametric and additive trees to proximity data by least squares methods. Behavior Research Methods, Instruments, & Computers. 16(6). 551–552. 2 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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