RT Journal Article
T1 Application of choice models in tourism recommender systems
A1 Almomani, Ameed Ali Ahmad
A1 Saavedra Nieves, Paula
A1 Barreiro, Pablo
A1 Durán Medraño, Roi
A1 Crujeiras Casais, Rosa María
A1 Loureiro García, María Luz
A1 Sánchez Vila, Eduardo
K1 Artificial intelligence
K1 Choice models
K1 Ensembles
K1 Knowledge engineering
K1 Recommender systems
K1 Tourism
AB Choice models (CM) are proposed in the field of tourism recommender systems (TRS)with the aim of providing algorithms with both a theoretical understanding of tour-ist's motivations and a certain degree of transparency. The goal of this work is toovercome some of the limitations of current state-of-art algorithms used in TRSs byproviding: (1) accurate preferences, which are learnt from user choices rather thanfrom ratings, and (2) interpretable coefficients, which are achieved by means of theset of estimated parameters of CM. The study was carried out with a gastronomicdata set generated in an ecological experiment in the tourism domain. The perfor-mance of CM has been compared with a set of baseline algorithms (rating-based andensembles) by using two evaluation metrics: precision and DCG. The CM out-performed the baseline algorithms when the size of the choice set was limited. Thefindings suggest that CM may provide an optimal trade-off between theoreticalsoundness, interpretability and performance in the field of TRS
PB Wiley
SN 0266-4720
YR 2022
FD 2022
LK http://hdl.handle.net/10347/30734
UL http://hdl.handle.net/10347/30734
LA eng
NO Almomani, A., Saavedra, P., Barreiro, P., Durán, R., Crujeiras, R., Loureiro, M., & Sánchez, E. (2023). Application of choice models in tourism recommender systems. Expert Systems, 40( 3), e13177. https://doi.org/10.1111/exsy.13177
NO This research was sponsored by EMALCSA/Coruña Smart City under grant CSC-14-13, the Ministry of Science and Innovation of Spain under grant TIN2014-56633-C3-1-R, the Ministry of Economy and Competitiveness of Spain under grant MTM2013-41383P, the Consellería de Cultura, Educación e Ordenación Universitaria (accreditation 2016-2019, ED431G/08), and the European Regional Development Fund (ERDF)
DS Minerva
RD 26 abr 2026