摘要:近年来，包含动态任务的交互式系统得到了广泛的应用.基于现有对用户与动态任务交互的研究，提出一个面向动态任务的定量化可计算的交互模型ICOM^DT，用于解释用户与动态任务的交互行为，并实现用户意图预测.更具体地，将ICOM^DT应用于运动目标选择任务，设计了两个实验以验证模型的有效性.实验1收集用户数据对模型进行拟合并预测用户选择的错误率，实验结果表明，能够很好地拟合且预测值也与真实值接近；实验2将模型对用户意图的理解拓展为一种辅助运动目标选择技术ICOMPointer，通过在具体的游戏场景中与Windows原本的选择技术及两种现有的增强目标选择技术对比，发现使用ICOMPointer选中目标的平均完成时间更短，完成速度更快.ICOM^DT模型的提出对计算机理解用户意图，提高用户与动态任务的交互效率有着重要意义.



Abstract:Interactive systems with dynamic tasks have been widely used recently. In this study, a computational interaction model ICOM^DT for dynamic tasks is proposed based on the existing research, which is used to describe interactive processes and predict user's intention. More specifically, ICOM^DT is applied to moving target selection, and two experiments are designed to verify the validity of the model. In the first experiment, user data is collected to fit the model and predict error rates. Results show that the proposed model fits the empirical data well and the predicted value is also close to the true value. In the second experiment, an assistant moving target selection technique ICOMPointer is achieved. By comparing with the basic selection technique and the other two state-of-the-art selection techniques in a game, it is found that ICOMPointer performs well. The ICOM^DT model is of great significance for computer to understand user's intentions and improve the efficiency of interaction between users and dynamic tasks.



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