Construction of a Smart Library Subject Precise Service Platform Based on User Needs

Abstract

Under the development and support of digital, networked and intelligent technologies (IT), university wisdom libraries adopt superb IT, sophisticated big data resource allocation, fine supervised wisdom RFD management system and exquisite supervised wisdom service system to provide a wisdom environment to meet users’ personalized needs and promote the transformation of libraries to a new form of wisdom. University intelligent libraries are still in their infancy and development stages in today’s world; the infrastructure has not been fully developed, the number of intelligent devices, the types of intelligent services, and the level of intelligence have all been developed but are still in their infancy and development stages, and the level of intelligence has not yet reached a significant level, and the level of intelligence has not yet reached a significant level. This paper develops the construction of a precise service platform for wisdom library disciplines based on users’ needs. In this paper, we propose a hybrid continuous ant colony optimization (BACO) method, and further propose a BACO-based multidoor image segmentation bun type for facial image segmentation. The experiments show that the proposed method has good performance and can lay the foundation for the next step of facial recognition and even the construction of smart library to ensure the accurate service of university smart library.