DocumentCode :
3166830
Title :
An intelligent recommender system for personalized fashion design
Author :
Zeng, Xuan ; Koehl, L. ; Wang, Lingfeng ; Chen, Yuanfeng
Author_Institution :
GEMTEX Lab., Univ. of Lille Nord de France, Roubaix, France
fYear :
2013
fDate :
24-28 June 2013
Firstpage :
760
Lastpage :
765
Abstract :
This paper originally proposes an intelligent recommender system for supporting personalized fashion design. Based on two models characterizing relations between human body measurements and human perceptions on human body shapes, we develop the criteria permitting to evaluate a set of new design styles for a specific garment customer and a desired fashion theme. In this approach, the intelligent techniques, including decision trees, cognitive maps and fuzzy relations computation, have been used.
Keywords :
clothing industry; customer services; decision trees; fuzzy set theory; recommender systems; cognitive maps; decision trees; fuzzy relations computation; garment customer; human body measurements; human body shapes; human perceptions; intelligent recommender system; personalized fashion design; Biological system modeling; Clothing; Computational modeling; Gravity; Recommender systems; Shape; Shape measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013 Joint
Conference_Location :
Edmonton, AB
Type :
conf
DOI :
10.1109/IFSA-NAFIPS.2013.6608496
Filename :
6608496
Link To Document :
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