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Analysis of Library User Behavior in the Context of Big Data

Author(s)

Shuai Wang

Affiliation(s)

Library, Hubei Minzu University, Enshi, Hubei, China

Abstract

In the context of rapid development and widespread application of big data technologies, a thorough analysis of library user behavior is crucial for optimizing services and enhancing resource utilization efficiency. This study aims to construct a framework for analyzing library user behavior within a big data environment, uncovering behavioral patterns and latent needs. Utilizing literature review to establish theoretical foundations, and employing data mining and statistical analysis methods, we conduct a multidimensional analysis of behaviors such as searching, borrowing, and browsing among library users. By developing a user behavior analysis model and integrating user profiling techniques, we explore influencing factors and evolving trends in user behavior. The findings demonstrate that big data technologies can accurately capture user behavior characteristics, revealing differences in information retrieval preferences and resource usage habits. This provides data support for libraries to formulate personalized service strategies, optimize collection layouts, and enhance service processes. Additionally, the study emphasizes the importance of data security and privacy protection in user behavior analysis, ensuring compliance and ethical soundness in the analytical process.

Keywords

Big Data; Library; User Behavior Analysis; Data Mining; Personalized Services

References

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