AI赋能机床数控技术及应用数字教材知识图谱构建研究OA

To advance the transformation of educational methods and technologies and in response to the"14th Five-Year"plan for the development of higher education textbooks in strategic emerging fields,this research aims to innovate the presentation of textbook content through the construction of a knowledge graph-based"CNC Machine Tool Technology and Applications"textbook.Using an entity-relationship semantic network,a knowledge system is established,forming a knowledge graph ontology model.Natural language processing and deep learning technologies are applied to mine knowledge from the textbook content,with algorithms filtering and extracting key knowledge points.Algorithms are used to filter and extract relevant information,while methods such as alignment,correlation,and merging based on the knowledge graph are applied to build a CNC knowledge graph.A knowledge base architecture is designed for efficient knowledge data storage,and open-source large language models,along with intelligent inference algorithms,are integrated to create a natural language recognition and intelligent reasoning model based on the CNC knowledge graph.Additionally,the"CNC Xiao Pu"intelligent Q&A system is developed.Leveraging a virtual teaching and research platform,this AI-driven approach facilitates cross-disciplinary integration and knowledge fusion,aiding teachers in their instructional activities and providing a tool that enhances students'independent learning capabilities.