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dc.contributor.authorTseng, Vincent S.
dc.contributor.authorLu, Hsueh-Chan
dc.contributor.authorTsai, Chia-Ming
dc.contributor.authorWang, Chun-Hung
dc.date.accessioned2009-08-23T04:51:08Z
dc.date.accessioned2020-05-29T06:38:43Z-
dc.date.available2009-08-23T04:51:08Z
dc.date.available2020-05-29T06:38:43Z-
dc.date.issued2008-07-23T01:45:00Z
dc.date.submitted2007-12-20
dc.identifier.urihttp://dspace.fcu.edu.tw/handle/2377/10769-
dc.description.abstractIn this paper, we propose a novel hybrid approach named Hybrid Behavior Pattern Mine (HBP-Mine) for analysis of patient behaviors by mining the RFID movement log. We first discover more about the regular behavior models using data mining techniques, then calculating the variation between different periods of regular behavior model. A number of studies have been done on the variations of association rule and sequential pattern in the past few years. In our approach, we are not only based on the variations of these two behavior patterns, but also integrated the other three kind of new behavior patterns using the weighted method. Finally, we conducted a series of experiments to evaluate the rationality of the proposed hybrid method under different system conditions by varying the parameters.
dc.description.sponsorship亞洲大學資訊學院, 台中縣霧峰鄉
dc.format.extent6p.
dc.relation.ispartofseries2007 NCS會議
dc.subjectData Mining
dc.subjectPatient Monitoring
dc.subjectAssociation Pattern
dc.subjectSequential Pattern
dc.subjectRFID
dc.subject.otherKnowledge Mining and Management
dc.titleA Hybrid Data Mining Approach for Analysis of Patient Behaviors in RFID Environments
分類:2007年 NCS 全國計算機會議

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