Design Of Personalized Recommendation System In Smart Education Information Platform

Based on the construction project of "Hebei smart education big data engineering research center",this research takes the personalized recommendation of education information as the research object,and focuses on how to improve the service level and wisdom level of the education information platform as the goal,and studies the design of personalized recommendation system.Firstly,the basic research on information platform,recommendation system and intelligent education is carried out to clarify the design objectives of the recommendation system in this study.Secondly,the system dynamics method is used to simulate the important factors that affect the effect of the recommendation system,such as the number of articles,the characteristic tags and the interest points of articles Design the recommendation system to obtain user information,article information,scene information of these three aspects of data level of the key data method;in the recommendation model part of the design of multi-channel recall mode,coordination of recall module and sorting module,at the same time,need to make the corresponding design for the common problems of the recommendation system,such as cold start,real-time,information "cocoon room";finally,push It is recommended that the system be tested to meet the preset requirements.The software carrier of the research results,Yizhixun app,in the actual test and use of nearly a year,it has constantly adjusted and optimized the overall platform and recommendation system to make it increasingly perfect.The results of this paper can also be used to guide the design of personalized recommendation system for other application platforms.