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A better understanding of the human user’s expectations and sensitivities to the real-time behavior generated by virtual agents can provide insightful empirical data and infer useful principles to guide the design of intelligent virtual agents. In light of this, we propose and implement a research framework to systematically study and evaluate different important aspects of multimodal real-time interactions...
In this paper we propose a sequential pattern mining method to analyze multimodal data streams using a quantitative temporal approach. While the existing algorithms can only find sequential orders of temporal events, this paper presents a new temporal data mining method focusing on extracting exact timings and durations of sequential patterns extracted from multiple temporal event streams. We present...
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