Accessing Alignments of Ontologies via IoT Based on SKOS Data Model

Many ontologies are provided to representing semantic sensors data.However,heterogeneity exists in different sensors which makes some service operators of Internet of Thing（IoT） difficult（such as such as semantic inferring,non-linear inverted index establishing,service composing） .There is a great d...

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Bibliographic Details
Published in:China communications 2017, Vol.14 (6), p.137-155
Main Authors: Liu, Xiulei, Hou, Xia, Yu, Junyang, Gao, Ying, Zhang, Yue, Zhang, Yingying
Format: Article
Language:English
Subjects:
Analytical models
Cognition
Data models
Inference algorithms
IOT
Ontologies
semantic sensor
Semantics
sensor ontology alignment
Sensors
SKOS
倒排索引
数据模型
服务组合
本体
物联网
语义推理
路线
集成传感器
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Summary:Many ontologies are provided to representing semantic sensors data.However,heterogeneity exists in different sensors which makes some service operators of Internet of Thing（IoT） difficult（such as such as semantic inferring,non-linear inverted index establishing,service composing） .There is a great deal of research about sensor ontology alignment dealing with the heterogeneity between the different sensor ontologies,but fewer solutions focus on exploiting syntaxes in a sensor ontology and the pattern of accessing alignments.Our solution infers alignments by extending structural subsumption algorithms to analyze syntaxes in a sensor ontology,and then combines the alignments with the SKOS model to construct the integration sensor ontology,which can be accessed via the IoT.The experiments show that the integration senor ontology in the SKOS model can be utilized via the IoT service,and the accuracy of our prototype,in average,is higher than others over the four real ontologies.
ISSN:1673-5447
DOI:10.1109/CC.2017.7961370