The Creation Of A Novel Recommendation System For Video Material On An E-Learning Platform

Recommendation systems are widely used to provide customized product suggestions for e-commerce and entertainment services. It is currently adopted in different businesses and has a growing interest in studies surrounding e-learning platforms. In this study, we used Sporting Edge Private Limited, a high-performing consultancy firm and e-learning provider, as a business case to transform their existing website into an AI-powered dynamic website, which uses a hybrid recommendation system to analyze their real-time data and provide dynamic recommendations. Initially, five research questions are formulated in the introduction section of the study, which are answered in the subsequent chapters. The literature review section studies six different categories of recommendation systems in detail.

Moreover, for algorithm selection for this study, four existing approaches used in previous recommendation systems were assessed. For this study's variable selection, seven variables previously used for building different recommendation systems are evaluated. Six metrics each are considered to understand how the success of the recommendation systems is measured in the past and how to measure the overall performance and business value of the recommendation system. The case study methodology was adopted in this research as it was suitable to answer each research question comprehensively as separate cases. The study primarily consists of implementing five different recommendation systems, which are implemented as carousels in the user interface of the company's website. Each of these five cases is elaborated along with the details of the implementation strategy used. After that, the performance of the recommendation system is evaluated in the website production environment. Through this process, different research questions are answered, new findings are discussed, and the future scope of the study is proposed.