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A classification method of reader borrowing data information in modern library based on top-k query algorithm

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成果类型:
期刊论文
作者:
Wei Huang;Jing Ling
作者机构:
[Wei Huang] Library, Hunan City University, Yiyang, 413000, China
[Jing Ling] Library, Xiangnan University, Chenzhou, 423000, China
语种:
英文
关键词:
top-k query algorithm;modern library;readers borrow data;information classification;maximum correlation minimum redundancy algorithm;polynomial naive Bayesian model.
期刊:
International Journal of Reasoning-based Intelligent Systems
ISSN:
1755-0556
年:
2025
卷:
17
期:
2
页码:
138-145
机构署名:
本校为第一机构
院系归属:
图书馆
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 in...

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