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- ArticleJanuary 2013
Transition Discovery of Sequential Behaviors in Email Application Usage Using Hidden Markov Models
HICSS '13: Proceedings of the 2013 46th Hawaii International Conference on System SciencesPages 2656–2665https://doi.org/10.1109/HICSS.2013.574Requirements monitors provide high-level feedback on software usage in real-time. Herein, we show how low-level monitoring can identify behavioral transitions that can be interpreted as learning transitions by a post-clinical team. One monitoring ...
- research-articleApril 2012
Discovery and diagnosis of behavioral transitions in patient event streams
ACM Transactions on Management Information Systems (TMIS), Volume 3, Issue 1Article No.: 4, Pages 1–28https://doi.org/10.1145/2151163.2151167Users with cognitive impairments use assistive technology (AT) as part of a clinical treatment plan. As the AT interface is manipulated, data stream mining techniques are used to monitor user goals. In this context, real-time data mining aids clinicians ...
- ArticleJanuary 2012
Pattern Discovery of User Interface Sequencing by Rehabilitation Clients with Cognitive Impairments
HICSS '12: Proceedings of the 2012 45th Hawaii International Conference on System SciencesPages 3001–3010https://doi.org/10.1109/HICSS.2012.467We 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. ...
- ArticleJanuary 2011
Diagnosing Stream-Mined Model Changes of Monitored Requirements for Cognitive Rehabilitation
HICSS '11: Proceedings of the 2011 44th Hawaii International Conference on System SciencesPages 1–11https://doi.org/10.1109/HICSS.2011.164Personalized 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 ...
- ArticleJanuary 2010
Monitoring Behavioral Transitions in Cognitive Rehabilitation with Multi-Model, Multi-Window Stream Mining
HICSS '10: Proceedings of the 2010 43rd Hawaii International Conference on System SciencesPages 1–10https://doi.org/10.1109/HICSS.2010.279This 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 ...
