| Using word embeddings to learn a better food ontology J Youn, T Naravane, I Tagkopoulos Frontiers in Artificial Intelligence 3, 584784, 2020 | 16 | 2020 |
| Organoleptic and Sensory Ontology. T Naravane, M Lange JOWO, 2017 | 7 | 2017 |
| Machine learning models to predict micronutrient profile in food after processing T Naravane, I Tagkopoulos Current Research in Food Science 6, 100500, 2023 | 4 | 2023 |
| Ontological Framework for representation of Tractable Flavor: Food Phenotype, Sensation, Perception. T Naravane, M Lange ICBO, 2018 | 3 | 2018 |
| Tripartite Flavour Model: Food Phenotype, Sensory and Interpretative Matrices. T Naravane, M Lange ISWC (P&D/Industry/BlueSky), 2018 | 1 | 2018 |
| Organolepticand Sensory Ontology T Naravanea, M Langeb | 1 | |
| Structure-property machine learning models with predictive capabilities for glycans in food T Naravane, G Simmons bioArxiv, 2023 | | 2023 |
| Ontological how and why: action and objective of planned processes in the food domain D Dooley, T Naravane Frontiers in Artificial Intelligence 6, 1137961, 2023 | | 2023 |
| Semantic lexicons: A new technique for predicting sensory perception J Cohen, T Naravane, R Ahn Brewing Summit 2018, 2018 | | 2018 |
Ilias TagkopoulosProfessor, Computer Science and Genome Center, University of California, DavisDirección de correo verificada de ucdavis.edu
