The application relates to the technical field of medical academic digital popularization, and specifically discloses an intelligent communication auxiliary method and
system for medical academic popularization, which comprises the following steps: acquiring multi-source communication data and analyzing and extracting business characteristics, constructing a cooperation partner portrait, converting the portrait and business project demand into a
semantic vector, calculating the similarity to screen a candidate cooperation partner set, calculating the
score through a comprehensive scoring function, generating a cooperation partner recommendation
list, real-time identification of compliance risks in business communication and pushing prompt information, automatic generation of targeted popularization language, collection of business feedback data for dynamic adjustment of the
weight coefficient of the scoring function. Through the closed-loop mechanism of multi-
source data fusion,
semantic matching, comprehensive scoring, compliance control and dynamic optimization, the application solves the problems of low screening efficiency, insufficient matching accuracy, high labor cost and high compliance risk of traditional methods, improves the
business efficiency and
communication quality of medical academic popularization, reduces the compliance risk, and realizes the intelligentization of the whole popularization process.