Study on Library Management System Based on Data Mining and Clustering Algorithm

Abstract

In order to improve the library's information retrieval and resource sharing capabilities and establish an intelligent library information management system, this paper proposes a library information management system development technology based on data mining technology. The system development is divided into two modules: library information retrieval and data mining algorithm design and software development of information management system. Using big data fusion and feature clustering methods to design intelligent information retrieval algorithm in library information management, establish library management database, carry out software development and design of library information management system in embedded environment, and finally carry out experimental test analysis. The test results show that using the method in this paper for library information management can improve the accuracy of book recommendation, which is 16.7% higher than the traditional method on average, and has good data mining and information retrieval capabilities. Performance indicators are better. Therefore, the algorithm is not only a means of automatic management of library systems, but also an effective means of realizing the modernization of library information.Povzetek: Sistem upravljanja knjižnice je nadgrajen z metodami strojnega rudarjenja in gručenja.

Big Data Clustering Techniques Challenged and Perspectives: Review

“…These approaches are applied to a single machine and only utilize this machine's resources. For single-machine techniques, data mining-based and dimension-reduction techniques are two common tactics [66]. , PAM [64], CLARA [27], and CLARANS [49].…”