Multi level Recommendation System of College Online Learning Resources Based on Multi Intelligence Algorithm

Abstract

Abstract In order to accurately grasp the actual search habits of online learning objects and establish a more reasonable multi-level recommendation scheme, a multi-level recommendation system of online learning resources in Colleges and Universities Based on multi intelligent algorithm is designed. With the help of the given topology, the multi-level recommendation behavior in the system is analyzed. Then combined with various types of Resource Recommendation application units, the hardware execution environment of the system is built. On this basis, a multiple intelligent neural network model is established. Combined with multi intelligent recommendation technology, the actual Resource Recommendation behavior related to learning objects is determined, and the software execution environment of the system is built. Combined with the structure of relevant hardware equipment, the design of multi-level recommendation system for online learning resources in colleges and universities based on multiple intelligent algorithms is completed. The experimental results show that the system designed in this paper records a larger number of learning objects, but the recommended waiting time is relatively shorter. The system can accurately grasp the actual search habits of online learning objects and establish a more reasonable multi-level recommendation implementation scheme.