3 papers
cs.IR2024
Greedy SLIM: A SLIM-Based Approach For Preference Elicitation
Claudius Proissl, Amel Vatic, Helmut Waldschmidt
Preference elicitation is an active learning approach to tackle the cold-start problem of recommender systems. Roughly speaking, new users are asked to rate some carefully selected…
cs.RO2020
Scalable Unsupervised Multi-Criteria Trajectory Segmentation and Driving Preference Mining
Florian Barth, Stefan Funke, Tobias Skovgaard Jepsen +1
We present analysis techniques for large trajectory data sets that aim to provide a semantic understanding of trajectories reaching beyond them being point sequences in time and sp…
cs.GT2018
Coordinating users of shared facilities via data-driven predictive assistants and game theory
Philipp Geiger, Michel Besserve, Justus Winkelmann +2
We study data-driven assistants that provide congestion forecasts to users of shared facilities (roads, cafeterias, etc.), to support coordination between them, and increase effici…