Combining Classification and User-Based Collaborative Filtering for Matching Footwear Size
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Otros documentos de la autoría: Alcacer Sales, Aleix; Epifanio, Irene; Valero, Jorge; Ballester, Alfredo
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Título
Combining Classification and User-Based Collaborative Filtering for Matching Footwear SizeFecha de publicación
2021Editor
MDPIISSN
2227-7390Cita bibliográfica
Alcacer, A.; Epifanio, I.; Valero, J.; Ballester, A. Combining Classification and User-Based Collaborative Filtering for Matching Footwear Size. Mathematics 2021, 9, 771. https://doi.org/10.3390/math9070771Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.mdpi.com/2227-7390/9/7/771/htmVersión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Size mismatch is a serious problem in online footwear purchase because size mismatch
implies an almost sure return. Not only foot measurements are important in selecting a size, but also
user preference. This is the ... [+]
Size mismatch is a serious problem in online footwear purchase because size mismatch
implies an almost sure return. Not only foot measurements are important in selecting a size, but also
user preference. This is the reason we propose several methodologies that combine the information
provided by a classifier with anthropometric measurements and user preference information through
user-based collaborative filtering. As novelties: (1) the information sources are 3D foot measurements
from a low-cost 3D foot digitizer, past purchases and self-reported size; (2) we propose to use an
ordinal classifier after imputing missing data with different options based on the use of collaborative
filtering; (3) we also propose an ensemble of ordinal classification and collaborative filtering results;
and (4) several methodologies based on clustering and archetype analysis are introduced as userbased collaborative filtering for the first time. The hybrid methodologies were tested in a simulation
study, and they were also applied to a dataset of Spanish footwear users. The results show that
combining the information from both sources predicts the foot size better and the new proposals
provide better accuracy than the classic alternatives considered. [-]
Publicado en
Mathematics 2021, 9, 771.Entidad financiadora
Ministerio de Ciencia, Innovación y Universidades | Universitat Jaume I
Código del proyecto o subvención
DPI2017-87333-R | UJI-B2017- 13 | UJI-B2020-22
Derechos de acceso
info:eu-repo/semantics/openAccess
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