Abstract
Due to the limited funds for the acquisition of university library resources, in order to improve the collection resource profitability and reduce the labor cost of libraries, a method of text classification using natural language processing is proposed to build an accurate procurement system for electronic book resources. Feature extraction is performed for the text information of the book collection, a feature vector matrix is established, and classification prediction is performed by machine learning algorithms. By optimizing the prediction model and evaluating the results with ten cross-validations, the accuracy of the LightGBM model testing reached 77.49%, so the acquisition system constructed based on this model can make effective decisions and thus optimize the structure of the collection resources.
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Acknowledgment
This paper is funded by Hunan Provincial Philosophy and Social Science fund project “Research on the Application of Artificial Intelligence Technology in Accurate Book Procurement in Universities under Smart Library” (21YBA179), and Education Department of Hunan Province of China (21C0595).
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Luo, K., Zhang, X. (2023). Research on the Construction of an Accurate Procurement System for Library e-Resources in Foreign Language Under Dig Data Analysis. In: Xu, Y., Yan, H., Teng, H., Cai, J., Li, J. (eds) Machine Learning for Cyber Security. ML4CS 2022. Lecture Notes in Computer Science, vol 13657. Springer, Cham. https://doi.org/10.1007/978-3-031-20102-8_48
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DOI: https://doi.org/10.1007/978-3-031-20102-8_48
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