Chinese Traditional Culture Learning System Based On Personalized Recommendation

The Internet injects new impetus into the traditional culture market,which makes the popularity of the traditional culture continue to increase,and the scale of the users increases rapidly.Chinese traditional culture education is becoming more and more important,and the country pays more and more attention to the study of traditional culture.The combination of Internet technology and traditional culture is the trend of the times.In recent years,the information explosion has increased,and the time spent by users to find items to meet their needs has increased.In order to solve this problem,personalized recommendation system emerges as the times require.The collaborative filtering algorithm is the most basic and core in the recommendation system,and the first algorithm is the most popular in the industry,but there are cold start and sparsity problems.In view of the above analysis,this paper designs and implements a Chinese traditional culture learning system based on personalized recommendation,which can not only be used as a platform for the display and promotion of traditional cultural resources,but also meet the individual needs of users.Improve the interest of users in traditional culture learning.The research contribution of Chinese traditional culture learning system based on personalized recommendation mainly includes the following three aspects.Firstly,the problem of data sparsity is mitigated by a tag-based collaborative filtering algorithm.Aiming at the problem of data sparsity in a traditional collaborative filtering algorithm,a tag-based collaborative filtering recommendation algorithm is adopted,And the data sparsity effect of the traditional collaborative filtering algorithm is improved.The time factor will affect the preference of the logged-in users to learn Chinese traditional cultural resources.The Exponential forgetting function is used to reduce the weight of user tags and reduce the impact of time on user interest.Secondly,a popularity-based recommendation algorithm is used to solve the cold start problem recommended by new users.In response to the cold start problem of new user recommendation,the popularity-based recommendation algorithm uses the popularity ranking of resources such as clicks and collections of resources in the traditional Chinese culture learning system based on personalized recommendation,and has made “the hottest” and “The latest"and other popular-based recommendation modules have achieved the effect of solving the cold start problem of new users.Thirdly,using the technical framework of Django+MySQL,the Chinese traditional culture learning system was designed to achieve personalized recommendation.In response to the diverse learning needs of different users,Django+MySQL's technical framework is used to design and implement a traditional Chinese tradition based on personalized recommendations,including classical books,cultural information,course videos,audio interpretation,cultural information and cultural categories.It enables the system to log in users to learn through video,audio and text reading,as well as to understand the current cultural forms and cultural policies through cultural information.Achieve the diversity of learning styles.