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dc.contributor.authorYu, Ching-Tzuen_US
dc.contributor.authorZou, Yu-Huien_US
dc.contributor.authorLi, Hao-Yuen_US
dc.contributor.authorLin, Szu-Yinen_US
dc.date.accessioned2019-05-02T00:26:46Z-
dc.date.available2019-05-02T00:26:46Z-
dc.date.issued2018-01-01en_US
dc.identifier.isbn978-1-5386-5059-2en_US
dc.identifier.urihttp://dx.doi.org/10.1109/IC3.2018.00-30en_US
dc.identifier.urihttp://hdl.handle.net/11536/151705-
dc.description.abstractIn a dynamic IoT environment, distributed sensors are used to collect real-time data continually. However, it is difficult to transform the dynamic data into a machine-readable and machine-interpretable form. we propose a semantic annotation approach to annotate sensor data via semantics. Firstly, this approach builds an ontology based on Semantic Sensor Network Ontology (SSN Ontology) for dynamic IoT sensor data. Then, the new knowledge is collected from input data by using the K-Means clustering, and to update the semantic information into the base ontology. The updated ontology forms the basis for semantic annotation.en_US
dc.language.isoen_USen_US
dc.subjectInternet of Thingsen_US
dc.subjectOntologyen_US
dc.subjectSemantic Annotationen_US
dc.subjectClusteringen_US
dc.titleAutomatic Clustering and Semantic Annotation for Dynamic IoT Sensor Dataen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/IC3.2018.00-30en_US
dc.identifier.journal2018 FIRST INTERNATIONAL COGNITIVE CITIES CONFERENCE (IC3 2018)en_US
dc.citation.spage188en_US
dc.citation.epage189en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000462080100041en_US
dc.citation.woscount0en_US
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