| Emergency management capability is a crucial component of national governance capability.The construction of the national governance system in the new era has put forward new requirements for the capabilities,institutions,and technologies of emergency management.From the perspective of information science research,how to comprehensively strengthen the emergency management systems and capabilities building,how to achieve the intelligence and precision of emergency management,and how to achieve knowledge-oriented smart services are urgent issues that need to be addressed.In addition,based on literature and field research,it has been discovered that emergency management activities still face problems such as low integration of emergency knowledge,coarse granularity of knowledge organization system concepts,and inefficient collaboration among emergency management departments.The organization of emergency knowledge organization is the foundation for realizing the informatization of emergency management.Therefore,research on the organization of emergency knowledge has become a highly concerned topic.This paper takes emergency text knowledge representation and organization as the research object.Based on a systematic review of relevant literature on emergency knowledge organization and knowledge reasoning,this paper uses content analysis,case analysis,and machine learning methods to study knowledge representation,knowledge reasoning and knowledge services,a knowledge-reasoning-oriented emergency knowledge base is established to provide high-quality emergency knowledge services for various users.The main conclusions of this paper are as follows:Firstly,the building of an emergency knowledge representation model.The emergency knowledge system is a conceptual term that describes the synthesis of emergency professional knowledge,and constructing an emergency knowledge system is the fundamental task for carrying out emergency knowledge representation.Initially,research and analyze the inherent elements and their relationships of emergencies,and the importance of explicit knowledge such as emergency plans and emergency cases in the emergency decision-making process was further clarified.Next,the provincial-level emergency plan for specific purpose was analyzed,from the perspective of the related policies.Based oncontent-analyzing method,the components of emergency cases were analyzed in this paper.Finally,in terms of emergency plans and emergency cases,a conceptual-level integration of emergency knowledge is what we would like to achieve.Based on the theory of knowledge elements,an emergency knowledge element model is constructed to extract knowledge elements such as emergency scenario knowledge elements,emergency resources,emergency actions,and emergency effects for emergency knowledge representation,providing a theoretical framework for subsequent research on emergency knowledge displaying and reasoning.Secondly,emergency knowledge representation based on multi-layer domain ontology.By analyzing and studying the theories,techniques,and methods of ontology modeling,we constructed an emergency knowledge ontology model for multi-layer domain ontologies,composed of upper level ontologies,domain ontologies and instance ontologies.Initially,the core concepts and attributes of ABC,SUMO and EVENT ontology models were introduced,the advantages and disadvantages were analyzed.Next,an emergency knowledge ontology model based on multi-layer domain ontologies was constructed for emergency domain knowledge representation.The construction process of the upper ontology,application ontology,and instance ontology of emergency knowledge was analyzed,and the instance ontology was taken as an example to verify the consistency and effectiveness of the multi-layer domain ontology model.Finally,the qualitative and quantitative evaluations of the emergency knowledge was performed.Thirdly,a corpus of the construction of an emergency knowledge for incidents to construted based on collective intelligence.The annotation method based on group intelligence significantly improved in annotation efficiency and quality compared to traditional manual annotation when facing a certain scale of corpus annotation tasks.This process not only requires fully utilizing the intelligence of each annotator,but also requires effective group collaboration,information discovery and intelligent aggregation.Initially,according to the ontology structure of emergency knowledge,establish annotation rules for emergency knowledge corpora corpus are established,laying a data foundation for the construction of emergency incident corpus;Next,a group intelligence based annotation model is proposed to provide theoretical support for the subsequent corpus annotation;Finally,using the data annotation platform Docanno,based on the ontology layer type names mentioned above,entity and relationship annotations were performed.The annotation results provide data support for subsequent entity recognition,relationship extraction,and knowledge inference.Fourthly,emergency knowledge reasoning that integrates semantic analysis and case-based reasoning.In order to achieve emergency decision-making and infer specific emergency response plans,this study proposes a knowledge graph based method to infer specific solutions.Initially,an emergency knowledge reasoning framework integrating semantic analysis and case-based reasoning was constructed,and the relationship between semantic analysis and case-based reasoning was elucidated.The basic semantic relationships were analyzed;Secondly,a knowledge graph inference model that integrates semantic analysis and case-based reasoning was established,including JSON data semantic analysis,historical case extraction,and case similarity calculation;Then,the mapping process between the ontology and the knowledge graph was established,and an emergency knowledge graph was constructed to store and query emergency knowledge,providing technical and data support for the establishment of the emergency knowledge base in Chapter7;Finally,case analysis was conducted.Typical emergency case events were selected to verify the usability of emergency knowledge reasoning results.Fifth,the construction of emergency knowledge base.The emergency knowledge base lays an important foundation for emergency decision-making,how to accurately characterize user information needs is the core issue of constructing an emergency knowledge base.Initially,based on the "means-end chain" theory,further analyze the user information requirements for emergency knowledge bases through content encoding,establishing correlation matrices,and drawing hierarchical value maps.Secondly,analyze the framework for constructing an emergency knowledge base for multi-agent needs,analyze the conceptual and logical structure design of the emergency knowledge base,and set the functional modules of the emergency knowledge base.The overall structure and function of the emergency knowledge base were designed based on user knowledge needs,on compessing both structured and unstructured storege processes;Finally,this system adopted the B/S network architecture mode and based on the Thymeleaf+Springboot2.X+Neo4j framework to develop an emergency knowledge base prototype system to meet the needs of emergency knowledge services.Sixthly,an emergency knowledge service strategy was proposed.With the aim of improving the level of emergency knowledge services,corresponding emergency knowledge service strategies were proposed from the three elements of emergency knowledge service subject,service object,and service platform,namely government,stakeholders,and emergency knowledge base platform.At the theoretical level,this study enriches the theory of knowledgeorganization,expands the research on methods of emergency knowledge representation and knowledge extraction,and broadens the application fields of knowledge bases.On a practical level,it promotes the intelligentization and precision of emergency management work,and enhances the government’s emergency management capabilities and service levels. |
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