Social event decomposition for constructing knowledge graph
- Authors
- Nguyen, H.L.; Jung, J.J.
- Issue Date
- Nov-2019
- Publisher
- Elsevier B.V.
- Keywords
- Event-driven knowledge graph; Independent component analysis; Social event decomposition; SocioScope framework
- Citation
- Future Generation Computer Systems, v.100, pp 10 - 18
- Pages
- 9
- Journal Title
- Future Generation Computer Systems
- Volume
- 100
- Start Page
- 10
- End Page
- 18
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/26389
- DOI
- 10.1016/j.future.2019.05.016
- ISSN
- 0167-739X
1872-7115
- Abstract
- Given the large amount of data collected from social media, it is very difficult for users to identify social events and understand their societies. In this paper, we propose a novel method for i)decomposing and discovering social events and ii)representing social events and their relationships as a knowledge graph. In particular, the proposed method is based on Independent Component Analysis (ICA)and the SocioScope Knowledge Graph (SKG)model. To demonstrate the actual performance, the proposed method has been evaluated with the support of the SocioScope framework (Nguyen and Jung, 2018). Then, it was verified that the system can efficiently provide people with a high understandability and traceability of social events. © 2019 Elsevier B.V.
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