2016-2017 Senior Project - Monetate Recommendation System
There are many ways to shop online. Wouldn’t it be easier if you had a friend shopping with you? Currently, many online recommendations show the most liked products rather than items that follow your taste or that are similar to items you are already viewed.
Using collaborative filtering and the Bayesian networks, the final algorithm will improve the process and recommendations of online shopping systems. With the algorithm, a user will get a contextual, behavior-based product recommendation. The algorithm will take into account different products and customers. Having a product recommended to you specifically, will make a much more effective and enjoyable shopping experience.
