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A semantic collaboration method based on uniform knowledge graph

Citation

Li, Q and Cao, Z and Tanveer, M and Pandey, HM and Wang, C, A semantic collaboration method based on uniform knowledge graph, IEEE Internet of Things Journal ISSN 2327-4662 (2019) [Refereed Article]


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DOI: doi:10.1109/JIOT.2019.2960150

Abstract

The Semantic Internet of Things is the extension of the Internet of Things and the Semantic Web, which aims to build an interoperable collaborative system to solve the heterogeneous problems in the Internet of Things. However, the Semantic Internet of Things has the characteristics of both the Internet of Things and the Semantic Web environment, and the corresponding semantic data presents many new data features. In this study, we analyze the characteristics of semantic data and propose the concept of a uniform knowledge graph, allowing us to be applied to the environment of the Semantic Internet of Things better. Here, we design a semantic collaboration method based on a uniform knowledge graph. It can take the uniform knowledge graph as the form of knowledge organization and representation, and provide a useful data basis for semantic collaboration by constructing semantic links to complete semantic relation between different data sets, to achieve the semantic collaboration in the Semantic Internet of Things. Our experiments show that the proposed method can analyze and understand the semantics of user requirements better and provide more satisfactory outcomes.

Item Details

Item Type:Refereed Article
Keywords:semantic internet of things, semantic collaboration, knowledge graph, internet of things, uniform knowledge graph
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Neural, Evolutionary and Fuzzy Computation
Objective Division:Defence
Objective Group:Defence
Objective Field:Intelligence
UTAS Author:Cao, Z (Mr Zehong Cao)
ID Code:136634
Year Published:2019
Deposited By:Information and Communication Technology
Deposited On:2020-01-11
Last Modified:2020-01-24
Downloads:0

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