# An Interactive Personalized Garment Design Recommendation System Using Intelligent Techniques
[EMAIL_ADDRESS] (Y.X)2 College of Fashion and Design, Donghua University, Shanghai 200051, China  
3 Key Laboratory of Clothing Design & Technology, Donghua University, Ministry of Education, Shanghai 200051, China  
4 Shanghai Belt and Road Joint Laboratory of Textile Intelligent Manufacturing, Shanghai 200051, China  
5 GEMTEX Laboratory, Ecole Nationale Superieure des Arts et Industries Tetitles, 59056 Roubaix, France; [EMAIL_ADDRESS] (X.T. ); [EMAIL_ADDRESS] (Y.Z. ); [EMAIL_ADDRESS] (P.B. )6 School of International Education, Zhejiang Sci-Tech University, Hangzhou 310018, China; [EMAIL_ADDRESS] (Correspondence: [EMAIL_ADDRESS] (Z.X. ); [EMAIL_ADDRESS] (J.W. )7 These authors contributed equally to this work. [PERSON]  
1 School of Textile and Garment, Anhui Polytechnic University, Wuhu 241000, China; [EMAIL_ADDRESS] (Z.W.). [EMAIL_ADDRESS] (Z.W.). [EMAIL_ADDRESS] (Y.X)2 College of Fashion and Design, Donghua University, Shanghai 200051, China  
3 Key Laboratory of Clothing Design & Technology, Donghua University, Ministry of Education, Shanghai 200051, Chinamany relevant computational tools, including recommendation systems [7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20], knowledge bases [21; 22; 23], decision-support systems [24; 25; 26; 27], and 3D virtual try-on technologies [28; 29; 30; 31; 32; 33] have been developed for solving various fashion design problems. For instance, to facilitate the general consumers in creating the preferred fashion design sketches, [PERSON] et al. developed an IGA-based knowledge model. They then presented a customized fashion sketch design support system [26]. [PERSON] et al. developed an intelligent system for fashion style selection for non-standard female figure types, combining a genetic algorithm and particle swarm optimization with a neural network classifier [34]. [PERSON] et al. proposed a recommendation model based on a hybrid method combining Kansei engineering with a traditional filtering algorithm to realize the personalized apparel recommendation services following users' emotional needs [12]. An open case-based color recommendation system was put forward by [PERSON] et al., enabling the helping of designers and consumers in obtaining the most appropriate color range of consumer products [9]. [PERSON] et al. created a fabric retrieval system for apparel e-commerce for designers based on Kansei technology [35]. For realizing jeans recommendation for a specific consumer, [PERSON] et al. created a jeans knowledge base and then set up a recommendation system using sensory evaluation and an intelligent data fusion method [21]. [PERSON] et al. developed an aesthetic-aware clothing recommendation system to perform clothing recommendations following the personalized aesthetic preference of consumers [13]. [PERSON] et al. explored an advanced apparel style learning and recommendation system that can recognize the deep design-associated features of clothes and learn the connotative meanings conveyed by these features as they relate to style and the body [14]. [PERSON] et al. put forth a new interactive designer-oriented, knowledge-based recommender system, permitting the generation and optimization of a fashion design scheme for a specific consumer accurately and quickly [10]. These research results provide good tools for advanced computational decision support to the fashion industry. However, for dealing with the particular challenges in garment design in terms of garment fit accuracy and efficiency, as well as garment appearances [36], the techniques mentioned above still showed some drawbacks, which are summarized as follows:  
* The techniques mentioned above are mainly oriented to consumers and are concentrated on fashion aesthetics, such as styles and colors. However, the garment recommendation systems integrating design elements for simultaneously dealing with fashion aesthetics and garment fit are still limited. Both garment fit and fashion style are the most crucial elements constituting the whole textile/apparel value chain [10].