Research And Application Of Collaborative Filtering Recommendation Algorithm In Digital Campus Platform Of Vocational Colleges

In the daily operation process,colleges and universities are making efforts to build a digital campus platform and develop a large number of information systems,which not only facilitates the majority of teachers and students,but also reflects the level of informationization of colleges and universities.The digital campus platform built by a vocational and technical college has accumulated a large amount of data,which makes it difficult for teachers and students to find the information that is really needed.For this reason,this paper explores the introduction of collaborative filtering recommendation algorithm into the digital campus platform to help teachers and students find useful information.The main contents of this thesis are as follows:(1)The collaborative filtering recommendation system and related technologies such as collaborative filtering concept,personalized recommendation algorithm working principle,Hadoop technology,Mahout and other technologies are summarized,and the two collaborative filtering technologies used in the paper are summarized.Memory-based collaborative filtering and model-based collaborative filtering are analyzed in detail,which lays a theoretical foundation for later research.(2)Analyze the various subsystems in the digital campus platform of the secondary vocational school,analyze the shortcomings in information search and utilization,extract and summarize the requirements of the recommended subsystem,and then from the functional requirements,data flow,system requirements Non-functional requirements are carried out in several aspects.(3)Based on the user's course selection information,frequently read book category information,and training performance information,the K-Means clustering algorithm is used to cluster the users,and a collaborative filtering recommendation model based on user behavior is established.Students recommend suitable elective courses,training courses,books,etc.(4)Based on the collaborative filtering recommendation model,the recommendation subsystem is designed and implemented,including the design and implementation of system logic function module,data acquisition module,collaborative filtering recommendation engine function module,etc.Filter the construction of the recommended subsystem of the recommendation algorithm.(5)Finally,the system is tested on the recommendation subsystem based on the collaborative filtering recommendation algorithm.At present,the recommendation subsystem has been integrated into the digital campus platform of a vocational college.After the student trial,students can quickly find the courses they want to take,the books they want to watch,and the exercises they want from the vast amount of information and numerous subsystems.The skills have improved the information processing level of the digital campus platform and won the praise of the majority of teachers and students.