Toward establishing a knowledge graph for drought disaster based on ontology design and named entity recognition

Abstract Drought disasters have caused serious impacts on the social economy and ecological environment, which are continuously increasingly exacerbated by climate warming other factors. disaster management usually involves processing a mass of isolated data from many fields expressed in different terminologies formats. These heterogeneous or so-called silos greatly hindered drought an information-rich manner. Establishing knowledge graph can facilitate reuse these provide references for management, ontology design named entity recognition two major challenges. Therefore, this study, we first designed recognizing concepts field their relationships, was implemented with modeling language. We next constructed corpus integrated model that built integrating multiple deep learning methods. Finally, applied to extract information CNKI literature database. The shows satisfactory results recognition. thus conclude combining technology toward establishing is promising.