Social event decomposition for constructing knowledge graph

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20
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24

초록

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.

키워드

Event-driven knowledge graph; Independent component analysis; Social event decomposition; SocioScope framework; Independent component analysis; Independent component analysis(ICA); Knowledge graphs; Large amounts; Social events; Social media; SocioScope framework; Understandability; Decomposition
제목
Social event decomposition for constructing knowledge graph
저자
Nguyen, H.L.; Jung, J.J.
DOI
10.1016/j.future.2019.05.016
발행일
2019-11
유형
Article
저널명
Future Generation Computer Systems
권
100
페이지
10 ~ 18