Recovering Individual Emotional States from Sparse Ratings Using Collaborative Filtering

A fundamental challenge in emotion research is measuring feeling states with high granularity and temporal precision without disrupting the emotion generation process. Here we introduce and validate a new approach in which responses are sparsely sampled and the missing data are recovered using a com...

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Detalles Bibliográficos
Autores principales: Jolly, Eshin, Farrens, Max, Greenstein, Nathan, Eisenbarth, Hedwig, Reddan, Marianne C., Andrews, Eric, Wager, Tor D., Chang, Luke J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Methods Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9743951/
https://www.ncbi.nlm.nih.gov/pubmed/36519147
http://dx.doi.org/10.1007/s42761-022-00161-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9743951/
https://www.ncbi.nlm.nih.gov/pubmed/36519147
http://dx.doi.org/10.1007/s42761-022-00161-2

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