Open AccessAnalysis on the Construction of Knowledge Graph of Mass Events Based on Ontology
Author(s) -
Binghua Ren,
Fanliang Bu,
Zhiwen Hou,
Yichun Fu,
Xiaoyuan Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1802/4/042056
Subject(s) - computer science , protégé , knowledge base , graph , ontology , construct (python library) , data science , graph database , event (particle physics) , domain knowledge , information retrieval , knowledge management , world wide web , theoretical computer science , semantic web , philosophy , physics , epistemology , quantum mechanics , programming language
Mass incidents pose a serious threat to public order and national security, building a knowledge base in the field of mass incidents, visualizing the relationship between entities from incidents, and scientifically reasoning about key information about incidents have become key links in effectively responding to mass violence crimes. In view of the lack of existing mass incident knowledge graph analysis methods and strong subjective reasoning methods, based on the BiLSTM-CRF model, this paper analyzes event elements and entity associations by extracting entities from the text data of mass events, the protege software is used to construct the mass event ontology model, and the visualization of the mass event knowledge graph is realized based on the neo4j graph database. The research results show that the knowledge graph established in this paper can better reflect the correlation between the elements in the mass incident, and is of great significance to the national security department to improve the emergency decision-making ability.