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Multi-expert Approval Opinion Integration of Government Information Project Based on Knowledge Fusion
Hua Bin,Wu Nuo,He Xin
(School of Science and Technology, Tianjin University of Finance and Economics, Tianjin 300222)
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[Objective]A short text integration method of multi-expert approval opinion in government information project is proposed through knowledge fusion, and the comprehensive opinion generation based on knowledge fusion of cognitive level is realized.

[Methods]Through the content mining of expert approval opinions, knowledge acquisition is completed. Exploit semantics of expert approval opinions in the entity hierarchy by target knowledge concept tree and custom method. And using domain ontology,knowledge fusion is realized at the micro and macro levels based on the text structure model. Then a comprehensive opinion brings up.

[Results] Compared with the original multi expert approval opinions, there is a increase of 0.19  vocabulary information among the comprehensive opinion generated based on knowledge fusion and  the average ratio of knowledge elements reaches 115.38%. It all shows the effectiveness of this method.

[Limitations]It is influenced by language specification of expert opinions and integrity of domain knowledge.

[Conclusions] By using scientific knowledge supplement and representation, the method in this paper shows better problem pertinence, knowledge coverage and generalization than the traditional short text integration method. And it also has achieved good application effects.

Key words Government information system      Project management      Opinion mining      Knowledge fusion      Text integration      
Published: 05 August 2021
ZTFLH:  TP391  

Cite this article:

Hua Bin, Wu Nuo, He Xin. Multi-expert Approval Opinion Integration of Government Information Project Based on Knowledge Fusion . Data Analysis and Knowledge Discovery, 0, (): 1-.

URL: 2021.0137     OR

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