Individuation of campus library service based on intelligent recommendation algorithm

This article focuses on the individualized service of campus library, the aim is to improve service quality and maximize resource utilization by employing intelligent recommendation algorithms. Based on the theory of individualized service and intelligent recommendation algorithm of campus library, this article designs an individualized service system covering system architecture, functional modules and algorithm models. Taking 500 students in a university as the object, the experiment was carried out, they were split into two groups: the test group and the comparison group. Individualized service system based on intelligent recommendation algorithm and traditional library recommendation service were adopted respectively. Through rigorous experimental verification, the findings indicate that the experimental group achieved a recommendation accuracy of 76% and a recall rate of 63.33%, both of which are considerably higher than the control group’s results (45% and 38.57%). These results demonstrate that the campus library's personalized service system, powered by the intelligent recommendation algorithm, is both practical and effective. It better aligns with user needs and offers viable solutions for the development of personalized services in campus libraries.