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2005
Springer

Data-Driven Refinement of a Probabilistic Model of User Affect

9 years 3 months ago
Data-Driven Refinement of a Probabilistic Model of User Affect
We present further developments in our work on using data from real users to build a probabilistic model of user affect based on Dynamic Bayesian Networks (DBNs) and designed to detect multiple emotions. We present analysis and solutions for inaccuracies identified by a previous evaluation; refining the model’s appraisals of events to reflect more closely those of real users. Our findings lead us to challenge previously made assumptions and produce insights into directions for further improvement.
Cristina Conati, Heather Maclaren
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where UM
Authors Cristina Conati, Heather Maclaren
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