2022/02/06 by Yashar Deldjoo, Deldjoo, Yashar, Fatemeh Nazary +11 · 6 citations
Arts and Humanities · Business, Management and Accounting · Psychology · #Color perception and design #Consumer Perception and Purchasing Behavior #FOS: Computer and information sciences #Fashion and Cultural Textiles #Information Retrieval (cs.IR)
paper · pdf · doi:10.48550/arxiv.2202.02757
openalex publication_date 2022/02/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The textile and apparel industries have grown tremendously over the last few years. Customers no longer have to visit many stores, stand in long queues, or try on garments in dressing rooms as millions of products are now available in online catalogs. However, given the plethora of options available, an effective recommendation system is necessary to properly sort, order, and communicate relevant product material or information to users. Effective fashion RS can have a noticeable impact on billions of customers' shopping experiences and increase sales and revenues on the provider side. The goal of this survey is to provide a review of recommender systems that operate in the specific vertical domain of garment and fashion products. We have identified the most pressing challenges in fashion RS research and created a taxonomy that categorizes the literature according to the objective they are trying to accomplish (e.g., item or outfit recommendation, size recommendation, explainability, among others) and type of side-information (users, items, context). We have also identified the most important evaluation goals and perspectives (outfit generation, outfit recommendation, pairing recommendation, and fill-in-the-blank outfit compatibility prediction) and the most commonly used datasets and evaluation metrics.