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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