Bridging the Gap Between Users and Recommender Systems: A Change in Perspective to User Profiling

One of the prevalent research challenges in the field of recommender system is to do better user profiling. There are some advanced user profiling techniques found in the literature to achieve the same. User profiling aims to understand the user well and as a result recommending the most relevant items to the user, where relevant means items returned as a result of intelligent techniques from various fields, mainly from data mining. This work is an attempt to answer the question "who understands a user the most?" The three obvious answers are Recommender System's high end approaches (e.g. data mining and statistical approaches), neighbors of the user or the user herself. The correct answer would be the last one, which is a user knows herself the best. In this direction, we propose to make users empowered and responsible for registering their preferences and sharing the same at their discretion. More personalized solutions can be offered when a user tells what she prefers and can contribute explicitly to the recommendation system's results generation. When a user is given the handle to communicate her preferences to the recommender system, more personalized recommendations can be given which are not only relevant (as tested by sophisticated evaluation matrices for recommender systems) but also plays wonder to users' satisfaction.