The Research of the Grouping Algorithm for Chinese Learners Based on Transitive Closure

In personalized education theory, each learner has different behavioral characteristics. From this perspective, the biggest shortcoming of the Chinese learning website is that it couldn’t reflect the individuality. Although some websites have classification of Chinese learners, most of them are based on the initial registration information. This paper proposes a grouping algorithm for Chinese learners based on transitive closure. The algorithm analyzes the user’s browsing behavior, we propose quantify the user’s access interest using web log, and use transitive closure clustering. We hope this method can provide a new idea for personalized in Chinese teaching.