Volume 9, Number 13, November 2019

Customized Garment Fashion Recommendation System using Data Mining Techniques

  Authors

Shukla Sharma¹²³, Ludovic Koehl¹², Pascal Bruniaux¹² and Xianyi Zeng¹², ¹GEMTEX, ²ENSAIT, ³ECOLE CENTRALE DE LILLE, France

  Abstract

Many fashion firms have enabled their business model to give extremely personalized experiences to their customers by using advanced CAD tools like CLO 3D, MarvelousDesigner, Browzwear, Lectra and many more for designing the garment and build a 3D avatar for the customized garment as well as web-based services to be integrated with the web and mobile-based applications. Due to the integration of highly advanced technologies for designing and giving personalized experience has increased the customer's expectations. In this paper, we have presented our initial work to build a garment fashion recommendation system for customized garments, which can be used with mobile and web applications. The proposed system structure is designed on the user's biometric profile and historical data of product order. We have collected the user’s historical data from a fashion company dealing with customized made-to-measure garments. Proposed architecture for recommendation system is based on different data mining techniques like clustering, classification and association mining.

  Keywords

Recommendation System, BIRCH, Adaptive Random Forest, Incremental learning, data mining, Association mining

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