Dirichlet Matrix Factorization: A Reliable Classification-Based Recommender System
dc.contributor.author | Lara Cabrera, Raúl | |
dc.contributor.author | González, Álvaro | |
dc.contributor.author | Ortega Ojeda, Fernando | |
dc.contributor.author | González Prieto, José Ángel | |
dc.date.accessioned | 2023-06-22T11:04:53Z | |
dc.date.available | 2023-06-22T11:04:53Z | |
dc.date.issued | 2022-01-24 | |
dc.description.abstract | Traditionally, recommender systems have been approached as regression models aiming to predict the score that a user would give to a particular item. In this work, we propose a recommender system that tackles the problem as a classification task instead of as a regression. The new model, Dirichlet Matrix Factorization (DirMF), provides not only a prediction but also its reliability, hence achieving a better balance between the quality and quantity of the predictions (i.e., reducing the prediction error by limiting the model’s coverage). The experimental results conducted show that the proposed model outperforms other models due to its ability to discard unreliable predictions. Compared to our previous model, which uses the same classification approach, DirMF shows a similar efficiency, outperforming the former on some of the datasets included in the experimental setup. | en |
dc.description.department | Depto. de Álgebra, Geometría y Topología | |
dc.description.faculty | Fac. de Ciencias Matemáticas | |
dc.description.refereed | TRUE | |
dc.description.sponsorship | Ministerio de Ciencia, Innovación y Universidades (España)/Fondo Europeo de Desarrollo Regional | |
dc.description.sponsorship | Comunidad de Madrid | |
dc.description.status | pub | |
dc.eprint.id | https://eprints.ucm.es/id/eprint/74845 | |
dc.identifier.citation | Lara Cabrera, R., González, Á., Ortega Ojeda, F. & González Prieto, J. Á. «Dirichlet Matrix Factorization: A Reliable Classification-Based Recommender System». Applied Sciences, vol. 12, n.o 3, enero de 2022, p. 1223. DOI.org (Crossref), https://doi.org/10.3390/app12031223. | |
dc.identifier.doi | 10.3390/app12031223 | |
dc.identifier.issn | 2076-3417 | |
dc.identifier.officialurl | https://doi.org/10.3390/app12031223 | |
dc.identifier.relatedurl | https://www.mdpi.com/2076-3417/12/3/1223/htm | |
dc.identifier.uri | https://hdl.handle.net/20.500.14352/72083 | |
dc.issue.number | 3 | |
dc.journal.title | Applied Sciences | |
dc.language.iso | eng | |
dc.page.initial | 1223 | |
dc.publisher | MPDI | |
dc.relation.projectID | PID2019-106493RB-I00 (DL-CEMG) | |
dc.relation.projectID | Convenio Plurianual with the Universidad Politécnica de Madrid in the actuation line of Programa de Excelencia para el Profesorado Universitario | |
dc.rights | Atribución 3.0 España | |
dc.rights.accessRights | open access | |
dc.rights.uri | https://creativecommons.org/licenses/by/3.0/es/ | |
dc.subject.keyword | Recommender systems | |
dc.subject.keyword | Collaborative filtering | |
dc.subject.keyword | Matrix factorization | |
dc.subject.keyword | Reliability | |
dc.subject.keyword | Classification model | |
dc.subject.keyword | Dirichlet distribution | |
dc.subject.ucm | Análisis funcional y teoría de operadores | |
dc.title | Dirichlet Matrix Factorization: A Reliable Classification-Based Recommender System | en |
dc.type | journal article | |
dc.volume.number | 12 | |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | c3011bfd-5025-4e49-8f0e-e16ea76da35c | |
relation.isAuthorOfPublication.latestForDiscovery | c3011bfd-5025-4e49-8f0e-e16ea76da35c |
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