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