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dc.contributor.authorErtek, Gurdal
dc.contributor.authorChi, Xu
dc.contributor.authorZhang, Allan N.
dc.date.accessioned2019-02-06T05:47:46Z
dc.date.available2019-02-06T05:47:46Z
dc.date.issued2017
dc.identifier.citationhttps://ieeexplore.ieee.org/abstract/document/7473879?section=abstracten_US
dc.identifier.urihttps://dspace.adu.ac.ae/handle/1/1521
dc.description.abstractA schedule-based system is a system that operates on or contains within a schedule of events and breaks at particular time intervals. Given RFID data from a schedule-based system, what set of actions and computations, and what type of data mining methods can be applied so that one can obtain actionable insights regarding the system and domain? The research goal of this paper is to answer this posed research question through the development of a framework that systematically produces actionable insights for a given schedule-based system. We show that through integrating appropriate data analysis methodologies as a unified framework, one can obtain many insights from even a very simple RFID dataset, which contains only very few fields. The developed framework is general, and is applicable to any schedule-based system, as long as it operates under a few basic assumptions. The types of insights are also general, and are formulated in the most abstract possible way. The applicability of the developed framework is illustrated through a case study, where real world data from a schedule-based system is analyzed using the introduced framework. Insights obtained include the profiling of entities and events, the interactions between entity and events, and the relations between events.en_US
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.subjectData miningen_US
dc.subjectDecision support systemsen_US
dc.subjectInformation systemsen_US
dc.titleA Framework for Mining RFID Data From Schedule-Based Systemsen_US
dc.title.alternativeIEEE Transactions on Systems, Man, and Cybernetics: Systemsen_US
dc.typeArticleen_US


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