Research On Information Recommendation Method Of Online Education Platform Based On User Preference Model

With the development of network technology,the education industry is no longer limited to offline,online classroom education is widely used.The rapid development of online education provides users with more abundant educational course resources and flexible learning methods.Various online education platforms are also constantly improving their service models to give users a better learning experience.However,at present,there are few personalized information recommendation services in online education platforms.The resources received by users are all the same,and it cannot be "tailored" according to students’ specific preferences.Information recommendation has been mature in other areas of application,the online education platform of information recommendation is a development trend of the future,it is also one of the pressing needs of the users,therefore,this study online education platform of information recommendation as the research direction and selection for higher education is a comprehensive online education platform as the research object,explore the information in the platform recommended method,makes every effort to optimize information recommendation service.This study reference information recommendation for online education resources at home and abroad research,the current research on online education direction and progress of the comb summary,compiled on the basic concept of online education,summarizes the information recommendation that is commonly used in several algorithms and their advantages and disadvantages,and recommended to use in the course of similarity calculation formula,To do a good job of sufficient algorithm and theoretical basis for the following research.Through literature research,it is found that most of the traditional information recommendation methods are based on the collection of user data through computer methods such as information mining and network tracking,and information recommendation is carried out by combining one or more methods.This study starts from the information recommendation method of online education platform,bases on user preference,conducts user survey by establishing user preference model,and recommends courses to users according to the guidance of the model.Firstly,according to the online education ranking list,a total of 16 comprehensive online education platforms for college students were selected for investigation,and the basic functions and recommendation functions of some current online education platforms were summarized to understand the current status of the functions of the platforms.Then,using the method of literature investigation and expert questionnaire method to determine the usefulness,reliability,into nature to dimensions of user preference model,and through the content analysis method to determine the interest include academic information,subject,the subject interest,media type,form,content,quality,application practice,acquisition cost,resources,time,learn basic 10 elements,Finally,the user preference model of online education platform information recommendation is determined.Finally,the experimental evaluation effectiveness of the model under the recommended,choose different professional 25 the students of grade,and belong to different specialty,the grade of 150 online education resources,are carried out in accordance with the various elements of the user preference model user preferences and resource investigation,and according to each user data and data resources for similarity calculation,Then,the top 10 courses with high similarity were pushed to the users to investigate their satisfaction.Then,the satisfaction results were analyzed.The results showed that the user satisfaction was good,indicating the validity of the user preference model to some extent.Based on user preferences,this study establishes a relatively targeted user preference model in online education resource recommendation,and verifies its feasibility and effectiveness to a certain extent.It provides another direction for online education information recommendation research,and has certain practical significance for improving online education information recommendation service.