Recommender systems

User preferences in recommendation algorithms: the influence of user diversity, trust, and product category on privacy perceptions in recommender algorithms

The use of recommendation systems is widespread in online com- merce. Depending on the algorithm that is used in the recommender system diferent types of data are recorded from user interactions. Typically, better recommendations are achieved when …

Digitale Mündigkeit

Junior Research Group funded by the NRW State Government. Project runtime from 2018 to 2022.

User Groups and Different Levels of Control in Recommender Systems

The aspect of control in recommender systems has already been extensively researched in the past. Quite a number of studies performed by various researchers reported that an increase in control had a positive effect for example on user satisfaction …

HCI for recommender systems: the past, the present and the future

How can you discover something new, that matches your interest? Recommender Systems have been studied since the 90ies. Their benefit comes from guiding a user through the density of the information jungle to useful knowledge clearings. Early research …

Towards interactive recommender systems with the doctor-in-the-loop

Recommender Systems are a perfect example for automatic Machine Learning (aML) – which is the fastest growing field in computer science generally and health informatics specifically. The general goal of ML is to develop algorithms which can learn and …