Interactive recommender system for images and video

Abstract

With the growth of the internet, e-commerce grew and flourished. With this, there was a need for predicting user’s desire. Recommending items or products to users that they may not have seen or acted upon. A recommender system employs collaborative filtering techniques to predict a user’s liking for a certain item. In this project, the aim was to develop an interactive system where it would take into account a user’s action on an item and constantly adjust its prediction based on this interactivity.