Fashion Recommendation Systems, Models and Methods: A Review

Informatics

Naimur Rahman Jeem¹  Deepayan Bardhan²  Edgar Lobaton²  Md. Saiful Hoque³  Samit Chakraborty⁴  Manik Chandra Biswas⁴ 

[1] Department of Computing Science, University of Alberta, Edmonton, AB T6G 2R3, Canada;Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27695, USA;Department of Textile Engineering, Daffodil International University, Dhaka 1207, Bangladesh;Wilson College of Textiles, North Carolina State University, Raleigh, NC 27695, USA;

关键词: fashion recommendation system;    e-commerce;    filtering techniques;    algorithmic models;    performance;   

DOI  :  10.3390/informatics8030049

来源: DOAJ

【 摘 要 】

In recent years, the textile and fashion industries have witnessed an enormous amount of growth in fast fashion. On e-commerce platforms, where numerous choices are available, an efficient recommendation system is required to sort, order, and efficiently convey relevant product content or information to users. Image-based fashion recommendation systems (FRSs) have attracted a huge amount of attention from fast fashion retailers as they provide a personalized shopping experience to consumers. With the technological advancements, this branch of artificial intelligence exhibits a tremendous amount of potential in image processing, parsing, classification, and segmentation. Despite its huge potential, the number of academic articles on this topic is limited. The available studies do not provide a rigorous review of fashion recommendation systems and the corresponding filtering techniques. To the best of the authors’ knowledge, this is the first scholarly article to review the state-of-the-art fashion recommendation systems and the corresponding filtering techniques. In addition, this review also explores various potential models that could be implemented to develop fashion recommendation systems in the future. This paper will help researchers, academics, and practitioners who are interested in machine learning, computer vision, and fashion retailing to understand the characteristics of the different fashion recommendation systems.

【 授权许可】

Unknown