Modeling Behaviour to Predict User State: Self-Reports as Ground Truth
University of Saskatchewan（萨斯喀彻温大学）
英文摘要：
Methods that detect user states such as emotions are useful for interactive systems. In this position paper, we argue for model-based approaches that are trained on user behaviour and self-reported user state as ground truths. In an application context, they record behaviour, extract relevant features, and use the models to predict user states. We describe how this approach can be implemented and discuss its benefits in comparison to solely self-reports in an application and to models of behaviour without the selfreport ground truths. Finally, we discuss shortcomings of this approach by considering its drawbacks and limitations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
