Intelligent student information management relies heavily on well-planned and executed management system architecture, yet poor design placement is a major roadblock. Intelligent student information management presents unique challenges that the tried-and-true ant colony algorithm fails to address, and its results are less than stellar. Consequently, this study analyses the management system and recommends its design and implementation based on ItemBizz+. To start, we use recommendation system theory to find the factors that will have an impact, and then we divide the indicators based on what the management system needs in order to minimize the factors that will interfere with its design and implementation. Then, the management system’s design and execution are thoroughly examined, and the recommendation system theory is used to create the ItemBizz + system. When comparing the two algorithms, ItemBizz + outperforms the classic ant colony approach and timeliness.