期刊：
International Journal of Reasoning-based Intelligent Systems,2025年17(2):127-137 ISSN：1755-0556
作者机构：
[Liping Zhong] Library, The Hunan City University, Yiyang, 413000, China
关键词：
decision tree algorithm;library digital resources;automatic classification;semantic similarity;the shortest distance;channel multiplication.
摘要：
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.
期刊：
International Journal of Reasoning-based Intelligent Systems,2025年1(1):66-72 ISSN：1755-0556
作者机构：
[Liping Zhong] Library, The Hunan City University, Yiyang, 413000, China
关键词：
binary sort tree;BST;E-book resources;search model;Vector space model;similar distance
摘要：
In order to solve the problems of low classification accuracy and large retrieval error in the classification and retrieval of e-book resources, a classification and retrieval method of e-book resources based on binary sorting tree is designed. Calculate the similar distance between e-book resource data and realise the structural analysis of e-book resource platform. The vector space model is introduced to realise the data integration of e-book resources. The retrieval model is constructed and the stability coefficient is introduced to realise the research. The experimental results show that the classification accuracy of the proposed method is about 99%, the retrieval error is always less than 1%, and the time cost is less than 2 seconds, which has certain advantages.
摘要：
In order to overcome the problems of low accuracy of classification results and long classification time in the traditional classification method of modern library reader borrowing data information, a modern library reader borrowing data information classification method based on top-k query algorithm is proposed. First of all, top-k query algorithm is used to collect library readers' borrowing data information and preprocess it. Then, combining the information gain algorithm and the maximum correlation and minimum redundancy algorithm, the second feature selection is performed for the data information borrowed by readers. Finally, the polynomial naive Bayesian model is used to realise the classification of library readers' borrowing data information. The experimental results show that the classification results using this method are accurate, the classification time is always within 11 s, the classification effect is good, and the application performance is good.
期刊：
International Journal of Reasoning-based Intelligent Systems,2025年17(1):66-72 ISSN：1755-0556
作者机构：
[Liping Zhong] Library, The Hunan City University, Yiyang, 413000, China
关键词：
binary sort tree;BST;E-book resources;search model;Vector space model;similar distance.
摘要：
In order to solve the problems of low classification accuracy and large retrieval error in the classification and retrieval of e-book resources, a classification and retrieval method of e-book resources based on binary sorting tree is designed. Calculate the similar distance between e-book resource data and realise the structural analysis of e-book resource platform. The vector space model is introduced to realise the data integration of e-book resources. The retrieval model is constructed and the stability coefficient is introduced to realise the research. The experimental results show that the classification accuracy of the proposed method is about 99%, the retrieval error is always less than 1%, and the time cost is less than 2 seconds, which has certain advantages.
