myBBC wanted to get a better understanding of the reasons users come to recommenders systems and their behaviour. For this project, I collaborated with a project lead and a UX Designer as my stakeholder whom I presented my work.
I focused on users’ motivations, rather than similarity algorithm capabilities. Therefore, I conducted a Desk Research in three different areas; academia, industry and previous work within the BBC.
BBC work focused mainly on similarity, trust and accuracy in recommender systems. However, most important academic papers and technical articles went beyond 'accuracy' and 'trust' as a purpose. Research suggests that user satisfaction is not always related to higher recommendation accuracy but in user experience as a whole.
Desk Research allowed me to understand the problem and develop five design key requirements for a personalised recommender engine.
The research resulted in a presentation of findings on novelty, conversational interaction UI, motivation and evaluation framework. It helped myBBC to find out more about the users’ motivations and information needs from a recommender system across different projects. The BBC R&D team warmly received the findings as more future oriented.