大语言模型驱动的题库自动生成:面向PDF的跨模态解析与知识点对齐OA

With the rapid development of online education,the automatic generation of high-quality question banks is increasingly urgent.The existing methods for automatic generation of question bank can be divided into two categories:the method based on textbook content has insufficient accuracy,while the method based on PDF question bank analysis has poor universality due to the diversity of formats.Therefore,a question bank generation system combining knowledge map and hybrid embedding is proposed,which uses multimodal PDF parsing technolo-gy to process text,formula and other heterogeneous content;Construct a map of knowledge points to realize the semantic association of ques-tion answer knowledge points;A hybrid matching algorithm is designed to fuse structural features and semantic features for precise alignment.The experimental results show that the proposed system achieves an accuracy rate of 70.68%in the question answer analysis matching task and 82.95%in the question knowledge point alignment task.The system has good universality and can be quickly applied to professional fields such as CFA examination,physician qualification examination,etc.after being combined with the teacher review mechanism.