UMAP 2019 - 27th Conference on User Modeling, Adaptation and Personalization

Intelligent User Interfaces aim to improve the interaction between computational intelligence and human intelligence. Computational intelligence supports different and complementary types of abilities than normally are available in the context of human-only cognition. Some of the previous work has found that humans do not always make the best possible decisions when working together with artificial intelligent systems. By designing and testing improved forms of support for interactive collaboration between human decision makers and artificial advice givers, we can enable decision making processes that better leverage the strengths of both collaborators. More generally the research in track can be characterised by exploring how to make the interaction between computers and people smarter, which may leverage solutions from data mining, natural language processing, novel interaction paradigms, and knowledge representation and reasoning.
Topics include (but are not limited to):
Adaptive personal virtual assistants (e.g., SIRI, Cortana, Alexa)
Adapting natural interaction (e.g., natural language, speech, gesture)
Transparency and control of decision support systems (e.g., semi-autonomous systems)
Tailored persuasion and argumentation interfaces
Tailored decision support (e.g., over- and under-reliance in uncertain domains)
Adaptive information visualization
Adaptive collaboration support
Novel methodologies for evaluating Intelligent User Interfaces
Case studies of real-world implementations