Title: Automatic classification of library digital resources based on decision tree algorithm

Authors: Liping Zhong

Addresses: Library, The Hunan City University, Yiyang, 413000, China

Abstract: Aiming at the problems of large classification error, low accuracy of feature extraction and long classification time in automatic classification of library digital resources, this paper designs an automatic classification method of library digital resources based on decision tree algorithm. First is to determine the maximum and shortest distance between digital resource data and aggregate the collected library digital resources. Then, the feature pyramid network structure is introduced and the channel multiplication method is used to extract the features of library digital resources data. Finally, construct the library digital resource data tree, determine the trunk and the critical degree of the library digital resource branches through entropy calculation, prune the unimportant branches, set up the library digital resource classifier, and realise the final automatic classification research. The test results show that the proposed method can reduce the classification error, and the classification effect is good.

Keywords: decision tree algorithm; library digital resources; automatic classification; semantic similarity; the shortest distance; channel multiplication.

DOI: 10.1504/IJRIS.2025.146934

International Journal of Reasoning-based Intelligent Systems, 2025 Vol.17 No.2, pp.127 - 137

Received: 22 Feb 2023
Accepted: 15 May 2023
Published online: 27 Jun 2025 *

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