Research and Practice of Personalized Learning Recommendation Based on Dynamic Community Discovery

Abstract

In view of the problems existing in the current online learning recommendation system, community discovery algorithms in complex networks are introduced to study the structure and evolution of learning communities, and learners' habits, learning behaviors, learning environments, learning tools and other factors are considered to discover and dynamically update the community; at the same times, it can provide community recommendations, community recommendation, knowledge resource recommendation, dynamic quality information sharing, to provide more intelligent services for learners, so as to promote the common development of users and communities.