Sebastian Sas Mangel Undergraduate Dissertation 2017/18

Preference Modelling in a News Application

Supervised by G.Struth

Abstract

In this age of information, people are overwhelmed by choice overload. This is especially true with online news, where social media platforms have been increasingly adapted as main sources of news content.

Recent developments regarding the alarming rate of fake news spreading on these platforms have raised more awareness in people, who feel more and more the need for a new and better way to gather news from trusted sources.

This student-proposed project is aimed at determining the business and technical aspects necessary to develop a news recommendation prototype. This software solution will offer an enjoyable and personal way for readers to gather news on the go. Additionally, a powerful analytics tool will be developed for news publishing companies in order to help them target the right customers. These goals have been set in the constraint of developing the recommendation system from scratch, without relying on pre-existing libraries or tools that offer implemented algorithms.