Design And Implementation Of Agriculture Intelligent Q&A System Based On Knowledge Graph

With the development of question answering system based on open domain knowledge graph,the Q&A system for professional domain is favored by many experts because it can improve the practicability of Q&A system by using a large amount of knowledge related to professional domain.Based on the relevant technologies of the open field Q&A system,this paper studies the agricultural Q&A system based on knowledge graph.The main work of this paper includes:First,construction of agricultural knowledge graph.Agricultural knowledge graph is not found in the biggest Chinese knowledge graph.Therefore,in this paper uses the construction technology of knowledge graph and ontology knowledge base,Scrapy and Protege tools,and collecting the agricultural data from the Internet to build a knowledge graph in agricultural field which covers crop varieties,crop pests and diseases,fertilizer and pesticide data.Secondly,the Q&A algorithm based on knowledge graph is designed and implemented.The Q&A algorithm is divided into two sub-tasks,named entity recognition and attribute linking.For the task of entity recognition,a multi-feature CRF in agricultural field is proposed to obtain the question entity.The CRF model training results for a feature,multiple feature combinations and the introduction of contextual information show that the CRF model which combines the selection word itself with the radical feature,and introduces a window context information has a good effect on the named entity recognition in the agricultural field.The value of F1 is 91.57%,and the accuracy rate is 97.05%for crop entities recognition.For the task of attribute linking,the bidirectional LSTM model is compared with the traditional one-way LSTM model,and the results show that the Bi-LSTM model can achieve better effect.Thirdly,the interactive Q&A system of agricultural knowledge is designed and implemented.It can support basic information query of crops and provide accurate answers to the question raised by users in the field of agriculture.