If you are interested in any aspect of systems that acquire information about a user (or group of users) so as to be able to adapt their behavior to that user or group, you have come to the right place! UM Inc. is a society of researchers and practitioners who are interested in developing adaptive systems and personalizing users’ experience with systems. Numerous applications of such systems exist for example in the area of natural language understanding and dialogue systems, in computer-based educational systems and online learning environments, in systems for computer supported collaboration, recommender systems for e-Commerce, news and entertainment.
The following paper has been chosen as the recipient of the 2015 James Chen Annual Award for Best Journal Article.
Dietmar Jannach, Lukas Lerche, Iman Kamehkhosh, Michael Jugovac
What recommenders recommend: an analysis of recommendation biases and possible countermeasures
UMUAI Vol. 25, issue 5, pp. 427–491
It was selected based on nominations from journal reviewers and editorial board members, and a subsequent comparative review by an award committee.
Best Paper Award
Predicting Individual Differences for Learner Modeling in Intelligent Tutors from Previous Learner Activities
Michael Eagle, Albert Corbett, John Stamper, Bruce Mclaren and Ryan Baker
James Chen Best Student Paper Awards
On the Value of Reminders within E-Commerce Recommendations
Lukas Lerche, Dietmar Jannach and Malte Ludewig
Analyzing and Predicting Task Reminders
David Graus, Paul Bennett, Ryen White and Eric Horvitz