计算机应用与软件2025，Vol.42Issue(5)：6-18,13.DOI:10.3969/j.issn.1000-386x.2025.05.002
基于有监督学习的问题生成综述
A SURVEY OF QUESTION GENERATION BASED ON SUPERVISED LEARNING
摘要
Abstract
Question Generation(QG)is one of the research directions of text generation in natural language processing.In this research,a machine is given a piece of text and an answer,and the machine processes the text and outputs one or more questions related to the current text and answer.At present,the research can be applied in a wide range of fields such as education,medicine and automated question and answer.However,research has shown that current supervised learning-based question generation methods still have many shortcomings.This paper described the development of the question generation,the general solution and process of the study.The paper analyzed the current state of research,divided question generation methods into four categories,and analyzed and compared the representative model architectures in each category.This paper summarized the technical challenges faced by problem generation technology and the future directions of development.关键词
深度学习/自然语言处理/有监督学习/问题生成Key words
Deep learning/Natural language processing/Supervised learning/Question generation分类
信息技术与安全科学引用本文复制引用
李玉娥,董黎刚,黄欣,蒋献..基于有监督学习的问题生成综述[J].计算机应用与软件,2025,42(5):6-18,13.基金项目
浙江省重点研发计划基金项目(2023C03202). （2023C03202）
