Web-based decision making using machine learning and recommender system: the case of exodus

Abstract

On a daily basis, each one of us is required to decide on a number of issues. Difficulty varies depending by the importance and the options of the decision. As the time passes by, technological advances help millions of users in decision making by creating new methods and tools that users can easily use and utilize. The aim of this study was to create an online platform that assists users in the case of exodus decision. To do so, state of the art technologies will be used including M.E.A.N (MongoDB, ExpressJS, AngularJS, NodeJS) stack and machine learning. Furthermore, the methods used are explained in detail as well as the reason M.E.A.N stack was selected against other available technologies. At the end of this research, the platform implemented was evaluated, providing users with an order list of best matching options for exodus based on the answers a user provided in a preceding questionnaire. In addition, this study evaluates the performance of machine learning in the domain of exodus selection. The research concludes with some results regarding the successful fulfilment of all research question. Also, we will provide some results of how machine learning reacted with the results given.