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dc.contributor.author
Armentano, Marcelo Gabriel
dc.contributor.author
Christensen, Ingrid Alina
dc.contributor.author
Schiaffino, Silvia Noemi
dc.date.available
2016-07-29T20:50:31Z
dc.date.issued
2015-06
dc.identifier.citation
Armentano, Marcelo Gabriel; Christensen, Ingrid Alina; Schiaffino, Silvia Noemi; Applying the technology acceptance model to evaluation of recommender systems; Center for Technological Design and Development in Computer Science; Polibits; 51; 6-2015; 73-79
dc.identifier.issn
1870-9044
dc.identifier.uri
http://hdl.handle.net/11336/6821
dc.description.abstract
In general, the study of recommender systems emphasizes the efficiency of techniques to provide accurate recommendations rather than factors influencing users' acceptance of the system; however, accuracy alone cannot account for users' satisfying experience. Bearing in mind this gap in the research, we apply the technology acceptance model (TAM) to evaluate user acceptance of a recommender system in the movies domain. Within the basic TAM model, we incorporate a new latent variable representing self-assessed user skills to use a recommender system. The experiment included 116 users who answered a satisfaction survey after using a movie recommender system. The results evince that perceived usefulness of the system has more impact than perceived ease of use to motivate acceptance of recommendations. Additionally, users' previous skills strongly influence perceived ease of use, which directly impacts on perceived usefulness of the system. These findings can assist developers of recommender systems in their attempt to maximize users' experience.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Center for Technological Design and Development in Computer Science
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc/2.5/ar/
dc.subject
Recommender Systems
dc.subject
Evaluation
dc.subject
User Acceptance
dc.subject
Technology Acceptance Model
dc.subject.classification
Ciencias de la Computación
dc.subject.classification
Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Applying the technology acceptance model to evaluation of recommender systems
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2016-07-29T18:33:03Z
dc.journal.number
51
dc.journal.pagination
73-79
dc.journal.pais
México
dc.journal.ciudad
Ciudad de México
dc.description.fil
Fil: Armentano, Marcelo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
dc.description.fil
Fil: Christensen, Ingrid Alina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
dc.description.fil
Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
dc.journal.title
Polibits
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.redalyc.org/articulo.oa?id=402641203011
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://ref.scielo.org/9gyp7y
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.17562/PB-51-10
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