Vogue Vision: Customized Apparel Recommender System Using Hybrid Approach

Recommendations significantly improve user experience across industries, particularly in fashion. These systems analyze user preferences and behaviors to offer personalized product suggestions. Content-based filtering matches products to user data for accuracy, while collaborative filtering leverages user data to suggest them using similar user preferences using SVD and correlation techniques. Vogue Vision combines these methods, averaging their outputs and interacting matrices to create hybrid recommendations. This paper details the design, implementation, and evaluation of a hybrid fashion recommendation system, demonstrating its effectiveness in boosting user satisfaction, collaboration, and sales by providing personalized apparel recommendations, showcasing the growing role of intelligence in fashion retail.