An intelligent garment recommendation ...
Type de document :
Article dans une revue scientifique: Article original
URL permanente :
Titre :
An intelligent garment recommendation system based on fuzzy techniques
Auteur(s) :
Zhang, Zhang [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie et Matériaux Textiles [GEMTEX]
Liu, Kaixuan [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie et Matériaux Textiles [GEMTEX]
Dong, Min [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie et Matériaux Textiles [GEMTEX]
Yuan, Hua [Auteur]
Wuhan Textile University
Zhu, Chun [Auteur]
Xi'an Polytechnic University
Zeng, Xianyi [Auteur]
Ecole nationale supérieure des arts et industries textiles de Roubaix (ENSAIT)
Génie et Matériaux Textiles [GEMTEX]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie et Matériaux Textiles [GEMTEX]
Liu, Kaixuan [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie et Matériaux Textiles [GEMTEX]
Dong, Min [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie et Matériaux Textiles [GEMTEX]
Yuan, Hua [Auteur]
Wuhan Textile University
Zhu, Chun [Auteur]
Xi'an Polytechnic University
Zeng, Xianyi [Auteur]
Ecole nationale supérieure des arts et industries textiles de Roubaix (ENSAIT)
Génie et Matériaux Textiles [GEMTEX]
Titre de la revue :
The Journal of The Textile Institute
Nom court de la revue :
J. Text. Inst.
Numéro :
-111
Pagination :
1324-1330
Date de publication :
2019-12-03
ISSN :
0040-5000
Mot(s)-clé(s) en anglais :
Recommendation system
fuzzy techniques
knowledge base
AHP
fuzzy techniques
knowledge base
AHP
Discipline(s) HAL :
Sciences de l'ingénieur [physics]
Résumé en anglais : [en]
Garment purchasing through the Internet has become an important trend for consumers. However, in various garment e-shopping systems, it systematically lacks personalized recommendations, like sales advisors in classical ...
Lire la suite >Garment purchasing through the Internet has become an important trend for consumers. However, in various garment e-shopping systems, it systematically lacks personalized recommendations, like sales advisors in classical shops, in order to propose the most relevant products to different consumers according to their body shapes and fashion requirements. In this paper, we propose a consumer-oriented recommendation system by fuzzy techniques and AHP, which can be used inside a garment online shopping system like a virtual sales advisor. This system has been developed by integrating the professional knowledge of designers and shoppers and taking into account consumers’ perception on products. It can effectively help consumers to choose garments from the Internet. Compared with other prediction methods, the proposed method is more robust and interpretable owing to its capacity of treating uncertainty.Lire moins >
Lire la suite >Garment purchasing through the Internet has become an important trend for consumers. However, in various garment e-shopping systems, it systematically lacks personalized recommendations, like sales advisors in classical shops, in order to propose the most relevant products to different consumers according to their body shapes and fashion requirements. In this paper, we propose a consumer-oriented recommendation system by fuzzy techniques and AHP, which can be used inside a garment online shopping system like a virtual sales advisor. This system has been developed by integrating the professional knowledge of designers and shoppers and taking into account consumers’ perception on products. It can effectively help consumers to choose garments from the Internet. Compared with other prediction methods, the proposed method is more robust and interpretable owing to its capacity of treating uncertainty.Lire moins >
Langue :
Anglais
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
ENSAIT
Junia HEI
ENSAIT
Junia HEI
Collections :
Date de dépôt :
2023-06-20T11:21:36Z
2024-03-05T14:58:10Z
2024-03-05T14:58:10Z