Discovery and diagnosis of behavioral transitions in patient event streams
ACM Transactions on Management Information Systems (TMIS)
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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, which provides personalized email clients, a kind of assistive technology, to aid client communications that facilitate activities of daily living. By using the simplified, customized system, clients can now email, whereas they could not previously. By continuously monitoring usage, the project is able continually adapt the software to a user's changing needs. Thus, monitoring software usage, particularly email event sequences, is important. This paper introduces theory and design of stream sequence-mining for UI event streams.