Observatorio de I+D+i UPM

Memorias de investigación
Artículos en revistas:
Cross-cultural contextualisation for recommender systems.
Año:2019
Áreas de investigación
  • Ingenierías
Datos
Descripción
Cultural Heritage (CH) domain is rapidly moving from traditional heritage sites into smart cultural heritage environment through various technologies. As one of the important technologies in the smart space, Recommender Systems (RSs) have been widely utilised to personalised services and matching visitors? goals and behaviours. Whereas, cultural difference is often considered a barrier to technology transfer or adoption. However, few studies focus on how the cultural factor influences recommendation despite cultural difference largely affects user preferences in the RSs. Furthermore, existing researches have mainly analysed evaluation results of their recommendation to reveal cultural differences, rather than utilising the cross-cultural factors into RSs. In this paper, we propose a novel concept of cross-cultural contextualisation and a model to compute the cross-cultural factor affecting users (countries or cultures) preferences by using matrix factorisation and clustering techniques. In addition, we discuss how to apply the model to RSs in CH domain through cross-domain recommendation techniques. Note that the two computational techniques were used to analyse cross-cultural factors which impact to user preferences, rather than to recommend items. In other words, the proposed model and computing results capable of utilisation into the other RSs as well as various research fields. Results of experiments with a real-world dataset showed effectiveness of the proposed model and supported that there is cultural difference influencing users? rating behaviours. Furthermore, a systematic analysis of dataset and the experimental results presented that individual users could be considered as country-wise groups for the model to analyse the cross-cultural factors.
Internacional
Si
JCR del ISI
Si
Título de la revista
Journal of Ambient Intelligence And Humanized Computing
ISSN
1868-5137
Factor de impacto JCR
4,594
Información de impacto
JIF: 4,594
Volumen
0
DOI
10.1007/s12652-019-01479-9
Número de revista
0
Desde la página
1
Hasta la página
12
Mes
SEPTIEMBRE
Ranking
26/136: Comp. Science & Art. Int.; 27/156: Comp. Science & Information Systems; 18/90 Telecommunications) (año 2019)
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Minsung Hong (Western Norway Research Institute, Vestlandsforsking)
  • Autor: Sojung An (Chung-Ang University,)
  • Autor: Rajendra Akerkar (Western Norway Research Institute, Vestlandsforsking)
  • Autor: David Camacho Fernandez (UPM)
  • Autor: Jason J. Jang (Chung-Ang University)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Sistemas Informáticos
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