Personalized Intelligent Recommendation of Cultural Resources Based on User Preference Collaborative Filtering Algorithm

With the rapid growth of user information, more and more netizens hope to obtain more comprehensive and effective useful resources through the Internet. However, the traditional information retrieval system can not meet the requirements of its very large amount of data, especially complex and extremely valuable because of the low efficiency of algorithm, low accuracy and limited database resources. Therefore, this paper proposes a collaborative filtering algorithm based on user preference to study the personalized recommendation of ethnic cultural resources. Firstly, this paper introduces the concept, function and characteristics of ethnic cultural resources, and then studies the collaborative filtering algorithm based on users' preferences. On this basis, the personalized recommendation framework of ethnic cultural resources is studied, and the operation performance of this framework is tested. The final test results show that the personalized recommendation method of ethnic cultural resources based on user preference collaborative filtering algorithm is different from other similar applications. Using the same attribute set for the same purpose can obtain more similarity information. Therefore, it can be seen that the personalized recommendation method of ethnic cultural resources based on user preference collaborative filtering algorithm can meet the basic needs.