Discovery and diagnosis of behavioral transitions in patient event streams
ACM Transactions on Management Information Systems (TMIS)
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This paper describes how quality metrics over stream-mined models can identify potential changes in user goal attainment, as a user learns a personalized emailing system. A sequence of mined models is generated from sequential segments of logged user email commands. When the quality of some models varies significantly from nearby models - as defined by quality metrics - then the user's behavior is flagged as a potentially significant change. This paper describes how this technique works in its application on a case study of cognitive rehabilitation via emailing.