Disaster Chain Mining And Visualization Analysis Based On Knowledge Graph

Geological disasters occur frequently in China.Various kinds of extreme geological disasters and their secondary disasters have aroused great research and concern of scholars and all circles of society at home and abroad.Carding it is helpful to grasp the current situation,hot spots and potential correlation among geological disasters.Most of the existing researches on disaster chain are based on the probability analysis method of simulation data and experimental data,and the space analysis method based on remote sensing image observation.As one of the key technologies in the era of big data,knowledge map provides a new method for disaster chain mining.In view of this,the research object of this study is the geological disaster literature and report text data in Wanfang data,China Knowledge Network and Sina Network,using UCINET and BICOMB literature analysis tools,with the help of Knowledge Atlas,in addition,K-core Algorithm and GN Algorithm are used to find the agglomerated sub-group and community structure of geological disaster domain atlas,and the latest frontier problems,research situation,disaster-forming environment and other aspects are emphatically analyzed,it also provides a new idea for mining the dominant geological disaster chain in different geological conditions.The main contents of this study include:(1)the construction and analysis of the knowledge map of co-occurrence of key words in geological disasters.The accurate extraction of text information is the key to guarantee the accuracy of knowledge expression and to construct the co-occurrence knowledge map.Key words can reflect the thesis and the topic of the article,so this paper extracts key words to represent the key information of the text.The process is as follows:to collect the text data of the literature and reports on the subject of geological disasters in Sichuan and Shandong Province,and to determine the source of the data to avoid data redundancy and waste of network resources;The time and place information of the statistical text is analyzed to obtain the data source with time and area mark,and the co-occurrence knowledge map of the key words of geological hazards is established,and the K-core analysis and community division are carried out.(2)establishing disaster co-occurrence map based on graph theory and extracting geological disaster chain.According to the co-occurrence relationship with geological disasters and provinces,the co-occurrence map of disasters can be constructed.By searching the optimal path among disasters with known coordinates,the regional dominant disaster chain under different geological conditions is explored.Finally,the similarity Matrix is used to judge the rationality of disaster propagation path.Based on the above Algorithm and Knowledge Atlas,this paper studies the geological hazards and related problems in Sichuan and Shandong provinces.It is concluded that the geological disasters in Sichuan Province are closely related to rainstorm,rain and snow,while those in Shandong Province are closely related to typhoon,temperature and rainfall.At the same time,it is concluded that Sichuan Province has formed an earthquake-dominated disaster chain,and Shandong Province has formed an Severe Tropical Storm and karst collapse-dominated disaster chain.