近年来，专利陷阱及后续的专利诉讼对技术创新的影响日益凸显，应对这一态势的重要手段是专利预警。专利申请书是最早公开的专利文献，以此为突破口，对申请书的特征字段进行分析，构建申请特征与专利诉讼的回归模型；研究表明，权利要求数、引用专利数和技术宽度与专利诉讼发生概率有显著的正向关系，是与专利诉讼密切相关的关键特征。因此，针对目标技术领域的相关专利，可以此回归模型为定量分析工具，筛选出易引发诉讼的高风险专利，从而利用最早公开的申请信息开展专利预警。

The impact of patent traps and following litigations on technology innovation has become increasingly prominent in recent years. Patent early-warning is an important method to coping with the situation. As the first published patent documentation, patent applications can be used as a breakthrough. By analyzing feature fields in patent applications, a regression model of application features and patent litigations is established. The results show that the probability of patent litigations has significant positive correlation with the number of claims, the number of citing patents and the width of technology, and they are key features closely related to patent litigations. Thus the regression model can be used as a quantitative analysis tool in targeted technology fields to screen out high-risk patents easily leading to litigations, and conduct patent early-warning by using the first published application information.