Construction Of Knowledge Graph Of Electromagnetic Compatibility Standards

With Semantic Web technology and Internet technology's rapid development,people are be-ginning to obtain information and knowledge from the Internet.With the gradual increase in data scale,it is difficult for traditional search engines to find accurate answers to questions and the answers' knowledge system.Therefore,a series of knowledge graphs represented by Google Knowledge Graph came into being.The purpose is to provide users with struc-tured knowledge rather than individual information points.The knowledge graph can signifi-cantly improve the accuracy of knowledge queries.The knowledge graph can also extend the boundary and scope of knowledge acquisition.The knowledge graph has received extensive attention from industry and academia.However,the knowledge graph still shows apparent deficiencies.The general knowledge graph has a comprehensive coverage but not enough depth,while constructing a knowledge graph in a professional field is time-consuming,la-borious,and inconvenient.In recent years,research on knowledge graphs has become popular.This is because the de-velopment of deep learning and neural network in semantic analysis makes it convenient to construct a knowledge graph.After constructing the knowledge graph,researchers can study the related applications of the knowledge graph:question answering system,recommenda-tion system,visual analysis.Based on the deep learning and neural network algorithms,this study extracts the document GJB151B-2013's data to construct a knowledge graph that serves the electromagnetic compatibility standard.The main research contents of this study are as follows:(1)This study analyzes the content of document GJB151B-2013 and stores it in an Excel file.This study creatively proposes storing picture links to store data in picture format in the knowledge graph.Then this study uses python to convert the Excel file into a CSV file and builds an electromagnetic compatibility standard knowledge graph based on the CSV file.This study uses python and echart to build a visualization website based on the knowledge graph of electromagnetic compatibility standards.The study analyzes the website's func-tional requirements and designs its overall structure and detailed design plan.This study completed the design of the website and tested all the functions of the website.The Knowl-edge Graph's visualization website allows users to perform semantic search and visual anal-ysis of electromagnetic compatibility standards.(2)This study uses a semi-automatic technology to construct the Chinese version of the knowledge graph of electromagnetic compatibility standards in Chapter 3.This study cal-culates the entity similarity of the extracted data using the algorithm and establishes a syn-onymous entity database to complete the knowledge fusion.In Chapter 3,the entities and relationships that complete the knowledge fusion are imported into Neo4j,and the knowl-edge graph is displayed using Cypher sentences in the Neo4j browser.Chapter 3 also de-signs a question-and-answer system based on the knowledge graph of the Chinese version of the electromagnetic compatibility standard.This study integrates the Chinese question an-swering system and the Chinese knowledge graph into the knowledge graph's visualisation website in Chapter 2.The purpose of this study is to design a knowledge graph application website integrating question and answer system,semantic search and visual analysis to help electronic engineers find the desired data and relationships more conveniently and quickly.