An intelligent recommender system for personalized fashion design
Xianyi Zeng, Ludovic Koehl, Lingkang Wang, Yongchen Chen · 2013
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.