A Multimedia Content Recommender System Using Table of Contents and Content-Based Filtering

In recent years, we have witnessed a rapid growth in the availability of digital multimedia on various application platforms and domains. Consequently, the problem of information overload has become more and more serious which causes a difficulty and time consuming for the users to locate and discovers the desired data. In this paper, we propose an architecture of a Multimedia Recommender system for Education videos that recommends relevant videos to the user based on Content-Based Filtering and the Table of Content of relevant books, that in turn will increase the dynamism and accuracy of the recommended multimedia data of their preference, preventing them from consuming time and effort in locating the desired video.