［目的/意义] 提出一种基于余弦相似度的专利文献与产业类目映射模型，模型拥有准确、高效和易拓展的优点，可为后续研究提供借鉴和参考。［方法/过程] 整理现有专利与产业类目映射方法，以2015年度中国科学院院所发明专利与《战略性新兴产业分类》为例，设计专利文献与产业类目映射模型并做映射实验，并根据映射成果评价模型。［结果/结论] 专利文献与产业类目映射模型通过自然语言处理技术自动化得到专利文献与产业类目的映射组合，可实现专利到产业及产业到专利的映射，且可节省大量人力成本并方便地进行映射类目细粒度的调整，适用于大部分专利与产业类目的映射。最后，指出该模型有待完善之处，并对下一步可拓展的应用领域进行探讨。

[Purpose/significance] This paper aims to propose a mapping model based on cosine similarity for mapping between patent documents and industrial classification. This model is accurate, efficient and scalable, which provides some references for the further research. [Method/process] After introducing the methods for mapping between patents and industrial classification, we designed a model for mapping between patent documents and industrial classification and completed the mapping between the 2015 annual patents of Chinese Academy of Sciences and the Classification of Strategic Emerging Industries. Then we evaluated this model according to the mapping results. [Result/conclusion] This model obtains the mapping results between patent documents and industrial classification automatically by the natural language processing technology and enables mapping between patents and industrial classification bi-directionally. The method saves a lot of labor costs and can easily adjust the fine-grained classification and be applied to most of the mapping between patents and industrial classification. Finally, improvements of the model are described. Some future application areas are also briefly discussed in this paper.