Abstract:In order to solve the problems of complex relationship of factors and mixed knowledge in the field of flower diseases and pests, combined with the knowledge organization and management technology of knowledge graph, a knowledge management method of flower diseases and pests based on knowledge graph was proposed. Firstly, according to the literatures, the flower diseases and pests control elements, including environment were extracted, the flower diseases and pests ontology model was constructed and stored in RDF to realize the control of knowledge standardization and integrity. Secondly, according to the text characteristics obtained from the analysis, the triple extraction framework was proposed which combined the “01” tagging method of head and tail entity separation, a lite bidirectional encoder representations from transformers (ALBERT) and cascade tagging model with part of speech features (CasPOSRel).Then using the custom RDF2PG mapping algorithm to complete the storage and management of flower diseases and pests knowledge. The experiments showed that the F1 value of the tagging methods, pretrained model and extraction model in proposed extraction framework was increased by 0.88, 4.90 and 8.57 percentage points compared with that of baseline methods, and the F1 value of the extraction result was 95.07%. The knowledge discovery showed that the knowledge management method effectively organized and managed the knowledge of flower diseases and pests, and helped the flower growers to carry out more effective pests control work.