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Knowledge graph fusion for smart systems: A Survey

Authors
Nguyen, H.L.Vu, D.T.Jung, Jason J.
Issue Date
Sep-2020
Publisher
Elsevier B.V.
Keywords
Big data; Disruptive technologies; Knowledge graph; Knowledge graph fusion; Smart systems
Citation
Information Fusion, v.61, pp 56 - 70
Pages
15
Journal Title
Information Fusion
Volume
61
Start Page
56
End Page
70
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/39690
DOI
10.1016/j.inffus.2020.03.014
ISSN
1566-2535
1872-6305
Abstract
The emergence of various disruptive technologies such as big data, Internet of Things, and artificial intelligence have instigated our society to generate enormous volumes of data. The effective, efficient, and transparent capture and fusion of knowledge from a massive amount data is becoming an increasingly popular and crucial topic. In this study, we aim to provide a broad, complete, and systematic overview of the definitions and challenges of the knowledge graph fusion, which represents a holistic approach for integrating, enhancing, and unifying knowledge graphs. Further, advanced techniques for handling knowledge graph fusion along with the pragmatic smart systems leveraging it are discussed as a part of multiple perspectives. We believe that this survey study can be used as a potential reference for system practitioners and researchers in surpassing current obstacles as well as shaping their future direction. © 2020 Elsevier B.V.
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소프트웨어대학 (소프트웨어학부)
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