Design And Implementation Of Intelligent Question And Answer System Based On Knowledge Graph Of Tea Diseases And Pests

Chinese climate is suitable for the growth of various types of tea trees,and tea is not only widely planted,but also covers a wide range of species,and has always been among the top countries in the world in terms of tea consumption and production.From the planting of tea trees to the processing of tea leaves,there are several stages,each of which requires knowledgeable guidance.Among them,pests and diseases can reduce the quality and harvest of tea leaves,which is an important factor limiting the development of the tea industry.With the expansion of tea planting area in recent years,the threat of pests and diseases to tea is gradually rising.The knowledge related to tea pests and diseases generally exists in the form of books or websites,and the data shows highly scattered and multi-source heterogeneous characteristics,so the relevant practitioners cannot get the tea diseases and pests knowledge quickly and accurately.Information can be obtained through search engines,but the generated results are generally various web links,which require their own screening and judgment,which is time-consuming and troublesome.When practitioners encounter tea pestrelated problems,it becomes a key task to obtain answers quickly and accurately.The emergence of knowledge graph provides a new direction for the question and answer system.Based on this,this paper uses techniques such as Natural Language Processing and deep learning to construct the knowledge graph of tea pests and diseases,and implement an question and answer system based on the knowledge graph.At present,the knowledge service of tea industry in China is not perfect,and the research of this paper is of great significance to promote the development of informatization and intelligence of tea industry.The specific research content of this paper contains the following three aspects:(1)Research on the construction method of tea diseases and pests knowledge graph.The process of knowledge graph is mainly divided into four steps: data acquisition,ontology construction,knowledge extraction and knowledge storage.To address the problems of highly scattered data,lack of annotated training corpus and high cost of knowledge graph construction in the field of tea pests and diseases.Firstly,use crawler technology to obtain tea diseases and pests data from relevant websites,and clean the data to obtain domain text content.Secondly,based on the characteristics of tea diseases and pests data content,a tea pest and disease ontology is constructed,with predefined entities and relationship types between entities,clear boundaries for data extraction,and data annotation on the basis of defining the ontology to obtain a text dataset of tea diseases and pests fields.Thirdly,the BERT-Bi LSTM-CRF model is used to train the produced dataset,and the trained model is used to perform automated triadic joint extraction of entities and relationships on unstructured data.The model is compared with several other common named entity recognition models to illustrate the advantages of the model.Finally,the extracted triplet data is stored in the Neo4 j graph database to achieve visualization of the knowledge graph.(2)Design of question and answer method based on tea diseases and pests knowledge graph.For the problems of question understanding and the difficulty of semantic linking from question to knowledge graph.On the basis that the tea diseases and pests knowledge graph has been constructed,a template and rule-based method is used to realize automatic question and answer.The information of tea pest names and aliases,and the keywords of question sentence classification are formed into a domain dictionary,and the Aho-Corasick algorithm is used to understand the intention and identify the entities of the question sentences.Finally,the Cypher statement dedicated to Neo4 j database is used to query the tea diseases and pests knowledge graph to obtain answers.Experiments have shown that if the type of input question is included in a predefined question type,the system can provide accurate answers to the question.The result of the answer depends entirely on the question type,the comprehensiveness of the template corpus coverage,and cannot be answered if there is no predefined.(3)Design and implementation of intelligent question and answer system based on tea diseases and pests knowledge graph.The system is mainly presented in the form of a web-based website.The system is based on the implementation of tea diseases and pests knowledge graph and question and answer methods,and combines Django,Echarts framework and HTML,Java Script and other technologies to realize the front and back-end interaction of the system.When the user asks a question,the system can accurately and quickly return the answer,saving the user’s time to filter the answer.