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Device-Oriented Automatic Semantic Annotation in IoT
Joint Authors
Liu, Fagui
Li, Ping
Deng, Dacheng
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-06-21
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Semantic technologies are the keys to address the problem of information interaction between assorted, heterogeneous, and distributed devices in the Internet of Things (IoT).
Semantic annotation of IoT devices is the foundation of IoT semantics.
However, the large amount of devices has led to the inadequacy of the manual semantic annotation and stressed the urgency into the research of automatic semantic annotation.
To overcome these limitations, a device-oriented automatic semantic annotation method is proposed to annotate IoT devices’ information.
The processes and corresponding algorithms of the automatic semantic annotation method are presented in detail, including the information extraction, text classification, property information division, semantic label selection, and information integration.
Experiments show that our method is effective for the automatic semantic annotation to IoT devices’ information.
In addition, compared to a typical rule-based method, the comparison experiment demonstrates that our approach outperforms this baseline method with respect to the precision and F-measure.
American Psychological Association (APA)
Liu, Fagui& Li, Ping& Deng, Dacheng. 2017. Device-Oriented Automatic Semantic Annotation in IoT. Journal of Sensors،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1187695
Modern Language Association (MLA)
Liu, Fagui…[et al.]. Device-Oriented Automatic Semantic Annotation in IoT. Journal of Sensors No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1187695
American Medical Association (AMA)
Liu, Fagui& Li, Ping& Deng, Dacheng. Device-Oriented Automatic Semantic Annotation in IoT. Journal of Sensors. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1187695
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1187695