Public Opinion Data Fusion Method based on Ontology Semantics

doi:10.23940/ijpe.19.11.p8.28992907

Int J Performability Eng ›› 2019, Vol. 15 ›› Issue (11): 2899-2907.doi: 10.23940/ijpe.19.11.p8.28992907

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Public Opinion Data Fusion Method based on Ontology Semantics

Pengju Wang^a,*, Huifeng Xue^a, Zhe Yu^b, and Feng Zhang^c

^aSchool of Automation, Northwestern Polytechnical University, Xi'an, 710072, China;
^bInformation Comprehensive Office, Yan'an Municipal Committee, Yan'an, 719000, China;
^cSchool of Information Engineering, Yulin University, Yulin, 719000, China

Submitted on ; Revised on ; Accepted on
Contact: * E-mail address: 416848742@qq.com
About author:Pengju Wang received his M.S. degree in computer science from Northwestern Polytechnical University and his Ph.D. from Northwestern Polytechnical University. His research interests include network public opinion analysis, data mining, and complex system modeling.Huifeng Xue received his Ph.D. in water resource economics from Xi'an Polytechnic University in 1995. He is currently a professor at Northwestern Polytechnic University. His research interests include complex system modeling, simulation and performance evaluation, management, systems engineering, energy and environmental systems engineering, computer control, intelligent control, and network control.Zhe Yu received her M.S. degree in Chinese language and literature from Northwestern University in 2005. She is currently a deputy director in the Information Comprehensive Office of Yan'an Municipal Committee. Her research interests include public opinion data analysis, data mining, and complex system modeling.Feng Zhang received his M.S. degree in computer science from Xidian University and his Ph.D. from Northwestern Polytechnical University. He is currently a professor at Yulin University. His research interests include cloud integrated manufacturing technology, complex system modeling, the Internet of things applications.

Abstract

Abstract: In order to improve the decision-making level for public opinion responses and realize the semantic fusion of multi-level and multi-source heterogeneous public opinion information, an ontology-based public opinion information fusion method is proposed. Firstly, aiming at quick response decision-making, the situation assessment model of public opinion information fusion is studied, and the information fusion system is constructed. The multi-level evaluation model of situation recognition, situation understanding, and situation prediction is formed. Then, the multi-indicator ontology model and method for public opinion decision-making are constructed, and the public opinion data fusion model based on ontology semantics is proposed, which realizes the relevance analysis and semantic fusion of domain knowledge. Finally, a multi-level public opinion data fusion model is constructed, and the construction of the underlying emergency information knowledge base to support the above functions is deeply studied. The simulation results show that the feasibility and efficiency of the situation assessment problem are solved by this method, the time complexity and space complexity of attribute reduction and value reduction are reduced, and the matching efficiency of situation assessment rules is improved.

Key words: situation assessment, information fusion, ontology semantics, public opinion decision, relevance analysis

Pengju Wang, Huifeng Xue, Zhe Yu, and Feng Zhang. Public Opinion Data Fusion Method based on Ontology Semantics [J]. Int J Performability Eng, 2019, 15(11): 2899-2907.

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Public Opinion Data Fusion Method based on Ontology Semantics

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