Title: Research on classification of educational digital resources based on KNN algorithm

Authors: Zizhen Xiao

Addresses: School of Fine Arts and Design, Yichun Early Childhood Teachers College, Yichun, 336000, China

Abstract: In order to overcome the problems of low classification accuracy and long classification time in traditional educational digital resources classification methods, a classification method of educational digital resources based on KNN algorithm is proposed. First, the crawler technology is used to automatically obtain educational digital resource data on the web page through the search engine, and store it in the resource library in a distributed manner. Then, the obtained educational digital resource data is pre-processed through cleaning, word segmentation and stop word removal. Then, according to the processing results, combined with chi square statistics and PCA methods, the characteristics of educational digital resources are selected twice. Finally, the results are selected according to the characteristics, K-nearest neighbour classification (KNN) algorithm is used to classify educational digital resources. The simulation results show that the proposed method has higher accuracy and shorter classification time.

Keywords: KNN algorithm; educational digital resources; crawler technology; Chi square statistical method; PCA method.

DOI: 10.1504/IJBIDM.2024.137733

International Journal of Business Intelligence and Data Mining, 2024 Vol.24 No.3/4, pp.352 - 363

Received: 18 Nov 2022
Accepted: 07 Mar 2023
Published online: 04 Apr 2024 *

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