1. Introduction
In the presence of information overload, scanning through all the available choices can be cumbersome. Humans make most decisions based on recommendations from a set of peers or seek out help from a professional. Collaborative Filtering (CF) systems automate the recommendation process by seeking out similar users and using the preferences of the common set of users to make recommendations regarding articles or items of potential interest to them [24]. Early CF systems required users to seek information from a known set of users. Automated CF systems (ACF) arose with the development of information retrieval techniques. These systems provide the user with recommendation without the user having to seek information [9].