In Japanese language instruction, teaching materials are highly significant and make the process of learning Japanese simpler. The general classification approach is ill-equipped to address the issue of inaccurately categorizing Japanese teaching materials; yet, this does provide light on resource categorization and makes it easier to get the necessary information. Therefore, this paper proposes a classification method based on density clustering algorithm for resource classification analysis. To start, in order to decrease the impact of resource classification as an intervening factor, indicators are categorized according to resource classification needs, and then Japanese language teaching materials are computerized. After that, it creates a system for classifying resources, sorts the outcomes of Japanese educational materials, and last, sorts the materials. Perform an exhaustive investigation. According to specified assessment criteria, the MATLAB simulation demonstrates that the classification approach based on the density clustering algorithm can properly categorize resources in Japanese language education. Resource categorization outperforms standard classification approaches in terms of efficiency.