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Integrating Expert Reviews for Government Information Projects with Knowledge Fusion |
Hua Bin(),Wu Nuo,He Xin |
School of Science and Technology, Tianjin University of Finance and Economics, Tianjin 300222, China |
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Abstract [Objective] This paper proposes a new method to integrate the short texts of multi-expert reviews for the same government information project, aiming to generate comprehensive opinion with knowledge fusion at the cognitive level. [Methods] First, we extracted knowledge from the reviews through content mining. Then, we analyzed semantics of these reviews with target knowledge concept tree and customized method. Third, we finished knowledge fusion at the micro and macro levels based on the text structure model and domain ontology. [Results] Compared with the original texts, the amount of information provided by our method was increased by 0.19, while the average ratio of knowledge elements reached 115.38%. [Limitations] The proposed method could be affected by the language of expert reviews and the integrity of domain knowledge. [Conclusions] Our new method could effectively integrate short texts from various fields.
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Received: 08 February 2021
Published: 23 November 2021
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Fund:Special Fund Project of Tianjin E-government Informatization(津党网信函(2018)146号) |
Corresponding Authors:
Hua Bin,ORCID:0000-0002-2411-3638
E-mail: bigsoon@sina.com
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