Fashion Fusion: Exploring Apparel Recommendation Systems across companies using Machine Learning Approach

Abstract

Recommendation technology is an advanced technology which gives users an improved service to get more information about a product. Fashion recommendation system is same as having a personal stylist who can recommend products based on user's preference. It uses data from users shopping history to recommend the trending outfits for making shopping easier. This paper aims to analyse a model for fashion recommendation system using K-Nearest Neighbor (KNN). Analysis of the services provided to the consumer like category, gender, and brand across companies should be relevant which helps in improving consumer overall shopping experience. Using Content-based Filtering the products are filtered based on user’s preference and out of all recommended products the one with highest rating product is predicted using Random Forest Regressor. The comparison between algorithms is made to take best of all, to enhance the performances.