摘要： 针对公共政策的语义分析对比是行政管理重要的研究方向，随着深度学习、知识图谱应用越来越广泛，任何在这一领域改进技术方法的尝试都可能带来较大的进步。将自然语言理解相关技术应用于产业政策研究有利于政策的制定与管理。针对软件产业政策提出一套基于自然语言理解的技术分析方法，旨在构建政策之间的关联关系网络，以期辅助政府决策。

中图分类号： TP301
文献标识码： A
DOI：10.16157/j.issn.0258-7998.212224
中文引用格式： 孙璐，薛强，张金言，等. 基于自然语言理解的软件产业政策关联性分析技术[J].电子技术应用，2021，47(12)：57-63.
英文引用格式： Sun Lu，Xue Qiang，Zhang Jinyan，et al. Relevance analysis technology of software industry policy based on nature language understanding[J]. Application of Electronic Technique，2021，47(12)：57-63.

Relevance analysis technology of software industry policy based on nature language understanding

Abstract： The analysis of public policy is vitally significant in administrative study. With the wide application of deep learning and knowledge graph, any effort to improve technique method in this area is likely to be of great benefit. Therefore, applying nature language understanding and other technology in industrial policy research is conducive, and will be critical to policy formulation and management. This article proposes a set of technical analysis method for software industry policy, aiming at constructing the relational relationship network among policies to assist government decision-making.

Key words : policy correlation analysis；knowledge graph；nature language understanding