Emotion Aware Recommender System

Abstract

In the realm of entertainment, it is having always been the priority to get the right stuff to the right person. This has been made significantly better through the establishment of recommender systems. These systems work on the principles of storing user data such as history, tags, cookies, and cache to try and suggest relevant media that one should find interesting. There has always been a problem with finding relevant information. Information retrieval systems and recommender systems were established to solve that problem but even in recommender systems there exists a 2D element of users and items which does not yield fully exceptional results. If we make it a 3D element by adding a third attribute which is the context of emotions, we can get results with more in-depth information.

Through this emotion awareness system, we will be able to detect a user’s emotions and will be able to propose recommendations based of those emotions. The development of this project will proceed in the fashion of FDD (Feature Driven Development) to accommodate for new features and applications on the run. The website for the system will be to showcase information about the actual recommender system. The mobile app will be the actual product that will be providing the recommender functionalities