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Construction and Verification of Knowledge Base of Political & Economy News based on Mixed Algorithm of Subgraph Feature Extraction and RESCAL

Volume 13, Number 8, December 2017, pp. 1268-1280
DOI: 10.23940/ijpe.17.08.p9.12681280

Pin Wu, Juanjuan Luo, Yonghua Zhu, Wenjie Zhang

Department of Computer Engineering and Science, Shanghai University, Shanghai, 200444, China

(Submitted on October 29, 2017; Revised on November 12, 2017; Accepted on December 3, 2017)


With the intelligent development of digital government management services and the advancement of Knowledge Graph study, it is necessary and possible to construct and verify a sound knowledge base of political and economic news to satisfy the users’ requirement of learning the information. Due to the high profession and diversity of political and economic news data, the entity link in the initially constructed knowledge base is lacking completeness. Meanwhile, the high frequency of data update leads to the iterative update of knowledge base. To address the problems, this paper builds a comparatively effective system in which we apply the reasoning results to the construction and iterative update of the political and economic news knowledge base. Then, a syncretic reasoning algorithm based on Subgraph Feature Extraction (SFE) and the factorization of a three-way tensor (RESCAL) is proposed to predict a link and accomplish the reasoning. Using the field data of political and economic news as a case of engineering application, the system we built effectively solves the incompleteness of the entity link in the initial knowledge base and the iterative update problem. The function of knowledge reasoning module and iteration module of knowledge base construction and autonomous updating system are verified by designing and implementing knowledge reasoning, as well as updating knowledge iteration. The experimental results demonstrate the effectiveness and feasibility of the functions of the knowledge base construction and autonomous updating system are verified.


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