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The development of socially interactive agents emerged as a challenging task due to paradigm shift from behavioral to motivational based agents. In current nascent scenario, machines may have their own motives and goals like humans, which subsequently enhance their capability to improve their communication during any social interaction. Moreover single general purpose learning is not applicable in...
We demonstrate the use of sequence pattern mining as applied to monitoring the usage of emailing software by clients with cognitive impairments. We show how Max Motif, a sequence-mining algorithm, can be applied using a stream-mining approach. Consequently, clinicians can now consider sequential patterns in their analysis of client emailing behaviors. Such analysis is part of the Think and Link project,...
Personalized requirements practices can be applied to specify goals as part of a clinical plan to aid cognitive rehabilitation. In this context, requirements monitoring can aid clinicians in tracking user behaviors as they attempt to achieve their goals. Quality metrics over stream-mined models can identify potential changes in user goal attainment, as a user learns his or her personalized emailing...
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