An automatic classification method of library archives data based on data mining

Article type: Research Article

Authors: Qiao, Li^{; *}

Affiliations: Shangqiu Institute of Technology, Shangqiu 476000, China

Correspondence: [*] Corresponding author. E-mail: jieluo@mls.sinanet.com.

Abstract: Aiming at the problems of poor accuracy of data feature extraction and large classification error in library archives data classification methods, an automatic classification method of library archives data based on data mining is designed. Firstly, the linear relationship between the characteristic variables of library archives data is determined, and the linear coefficient of archives data characteristics is calculated; Then, the characteristic states of library archives data are divided into three states, the characteristic data are normalized, and the adaptive differential evolution algorithm is used to remove the noise in the characteristics of library archives data; Finally, the mapping relation training model in data mining is used to input the data feature training set, and the file data features are labeled according to different weights; Establish automatic data classification model. The experimental results show that the highest accuracy of this method is about 97%.

Keywords: Linear relation, normalization, data processing, library archives: automatic classification, information entropy

DOI: 10.3233/WEB-210487

Journal: Web Intelligence, vol. 20, no. 2, pp. 123-131, 2022