[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.
华斌, 吴诺, 贺欣. 基于知识融合的政务信息化项目多专家审批意见整合*[J]. 数据分析与知识发现, 2021, 5(10): 124-136.
Hua Bin, Wu Nuo, He Xin. Integrating Expert Reviews for Government Information Projects with Knowledge Fusion. Data Analysis and Knowledge Discovery, 2021, 5(10): 124-136.
(General Office of the State Council. Construction Management Measures of National Government Informatization Projects[EB/OL]. [2020-08-20]. http://www.gov.cn/zhengce/content/2020-01/21/content_5471256.htm.)
(National Standards Commission, National Development and Reform Commission, Office of the Central Cyberspace Affairs Commission. Definition and Scope of Government Information System[EB/OL]. [2020-08-20].https://wenku.baidu.com/view/2088fe392a160b4e767f5acfa1c7aa00b42a9d1d.html?fixfr=FI3ZbuFXkNsHOwhOKiTb8g%253D%253D&fr=income1-wk_go_search-search.)
(ZW/T 1001-2019, Quality Requirements and Evaluation Specification for E-Government System Construction[S]. Beijing:The State Information Center, National E-Government Quality Supervision and Inspection Center, 2019.)
(ZW/T 1002-2019, Quality Requirements and Evaluation Specification for E-Government System Operation[S]. Beijing: The State Information Center, National E-Government Quality Supervision and Inspection Center, 2019.)
(ZW/T 1003-2019, Evaluation Specification of E-Government System Integration and Sharing[S]. Beijing:The State Information Center, National E-Government Quality Supervision and Inspection Center, 2019.)
(ZW/T 1004-2019, Technical Requirements and Evaluation Specification for E-Government Data Center[S]. Beijing:The State Information Center, National E-Government Quality Supervision and Inspection Center, 2019)
(Yang Zhen, Lai Yingxu, Duan Lijuan, et al. Short Text Sentiment Classification Based on Context Reconstruction[J]. Acta Automatica Sinica, 2012, 38(1): 55-67.)
(Sheng Suping, Liu Chunyan, Zhao Xinli. Compilation and Application System Development of E-Government Thesaurus[J]. China Information Review, 2006(3): 37-39.)
(Zhang Wei, Wang Hao, Deng Sanhong, et al. Research on Hierarchy Identification of Chinese Terms in the Field of E-government[J]. Journal of the China Society for Scientific and Technical Information, 2021, 40(1): 62-76.)
(Wang Ting, Ji Fujun. Automatic Modeling of Large-Scale Domain Ontology Based on Thesauruses and Online Encyclopedias[J]. Journal of the China Society for Scientific and Technical Information, 2017, 36(7): 723-733.)
(Li Fang, Xu Deshan. Construction of Chinese Domain Ontology on E-government Services Integration[J]. Journal of Modern Information, 2016, 36(1): 79-83.)
(Liu Xiaojuan, Li Guangjian, Hua Bolin. Knowledge Fusion: From the Conceptual Understanding to the System Construction[J]. Library and Information Service, 2016, 60(13): 13-19, 32.)
(Qiu Junping, Yu Houqiang. Research Progress and Trends of International Knowledge Fusion at the Perspective of Knowledge Science[J]. Library and Information Service, 2015, 59(8): 126-132, 148.)
(Wang Zhongyuan, Cheng Jianpeng, Wang Haixun, et al. Short Text Understanding: A Survey[J]. Journal of Computer Research and Development, 2016, 53(2): 262-269.)
(Wang Zhongqun, Huang Subin, Xiu Yu, et al. Research on Metrics-Model for Online Product Review Depth Based on Domain Expert and Feature Concept Tree of Products[J]. New Technology of Library and Information Service, 2015(9): 17-25.)
(Sun Yudi, Zhang Yuqiang. Research of Synjournal Evaluation Automatic Generation System Based on Ontology[J]. Journal of Intelligence, 2007, 26(2): 31-33.)
(Zhu Zhenyuan. Content Mining and Integration Study of Online Book Reviews Based on Information Classification[J]. Library and Information Service, 2016, 60(1): 114-124.)
[20]
张良, 蔡生. 信息量的度量及应用[J]. 沈阳大学学报, 2004, 16(2): 89-91.
[20]
(Zhang Liang, Cai Sheng. Measurement and Application of Information Quantity[J]. Journal of Shenyang University, 2004, 16(2): 89-91.)
(Hua Bin, Wu Nuo, Li Ruoxuan. Research and Practice of E-Government Project Evaluation Method Based on Knowledge Graph[J]. Information Studies: Theory & Application, 2021, 44(2): 147-153, 146.)
[24]
Choi S, Yoon J, Kim K, et al. SAO Network Analysis of Patents for Technology Trends Identification: A Case Study of Polymer Electrolyte Membrane Technology in Proton Exchange Membrane Fuel Cells[J]. Scientometrics, 2011, 88(3): 863-883.
doi: 10.1007/s11192-011-0420-z
[25]
Abdulghafour M, Chandra T, Abidi A. Data Fusion Through Fuzzy Logic Applied to Feature Extraction from Multi-Sensory Images [C]//Proceedings of IEEE International Conference on Robotics and Automation. 1993: 359-366.