基于多源数据融合的军事医学机构名称规范研究

分析多源数据融合背景下现有军事医学机构名称规范研究存在的问题，针对军事医学机构名称获取困难、构词特殊等特点，提出了一种实现军事医学机构名称规范的阶段性、特征性和语义化相结合的多源数据融合方法，为重点建立神经网络模型来融合不同来源数据打下初步基础。

Multisource data fusion-based normalization of military Medical institution names

Through the introduction of multi-source Information and multi-source data fusion, the research status and problems of the existing name authority in the context of multi-source data fusion are analyzed. Aiming at the characteristics of difficulty in obtaining names of military medical institution and special word formation, the article proposes a multi-source data fusion method that realizes the combination of the stage, characteristic and semantic of the name authority of military medical institutions. The next step is to focus on establishing a neural network model to fuse data from different sources.