Construction of knowledge graph of forest musk deer based on BiLSTM-CRF model and DPA method
Chuqiao Yang, Haiyan Wang, Jingyan Sai, Peiwei Zhang, Mengyao Yan · IOP Conference Series Earth and Environmental Science · 2020
Abstract Forest musk deer is a national key protected species, but due to overhunting and habitat destruction, wild musk deer has disappeared in large areas. Constructing a knowledge graph in the field of forest musk deer can standardize the relevant knowledge in the field of forest musk deer and lay a good foundation for wildlife protection and ecological construction. In order to construct the knowledge map of the forest musk deer, the entities were further subdivided first, and the BiLSTM-CRF model was used to identify the entities of the BIO-labeled data. After analysis, it was found that the model used in the experiment performed better. Secondly, the Dependency Parsing Analysis method was used to identify the relationship, and the relationship between the entities was smoothly extracted.Finally, the Neoj4 graph database was used to realize the storage and visualization of the knowledge graph of the forest musk deer. This research transforms the unstructured text in the field of forest musk deer into structured data. Through the systematic sorting of relevant knowledge in the field of forest musk deer, it can provide wildlife protection, artificial breeding of forest musk deer, intelligent knowledge services and other aspects some new technical means in the field of forest musk deer.