Unreliable Decision-Making and its Impact on Recommendation and Personalisation - perspectives from metrology and neuroscience -[go to overview]
One of the most important concerns in the field of adaptive information systems is to model human behaviour in order to offer personalisation and recommendation. This usually involves implicit or explicit knowledge about a user's preferences and behavioural patterns.
In this talk, I report on the lack of reliability of explicit user feedback and its interpretation in the light of system evaluation. By using probabilistic perspectives as used in metrology and physics as well as neuroscientific theories of the Bayesian brain, I will introduce novel user models with more empathy for the human nature. By means of user experiments and simulations, I will show that this information can be used to improve the standard collaborative filtering.
03.05.18 - 10:15