Many projects are being performed on campus and during these projects many interesting services are made. This makes it tricky for users to know of the existence of these services and to choose the right services based on their needs.

The goals of this project is to develop a service recommender system, comparable with the Netflix approach, that is able to recommend the user a set of services based on their past behaviour. The services might include all things that will happen on the campus, like sports, group activities, social and practical support and more.

The challenge is that PeCaflix is able to learn from data from very heterogeneous sources, like your social network data, phone data, biomedical sensing data. Another challenge is that it is able to connect people with similar profiles and actively suggesting them new ideas for joined activities.

For this project collaboration is needed with several groups from CTIT, biomedical engineering and behavioural science.