Title: Knowledge mapping-based online teaching resource recommendation method for Chinese education

Authors: Huishuang Qi

Addresses: School of Humanities, Puyang Vocational and Technical College, Puyang 457000, China

Abstract: In order to overcome the problems of poor recommendation accuracy, low recommendation recall and long recommendation time in traditional teaching resource recommendation methods, a knowledge map based Chinese online teaching resource recommendation method is proposed. First, the TF-IDF method is used to calculate the weighted value of Chinese education recommended resources, and then the ontology of the knowledge map of Chinese education online teaching resources is designed to obtain the representation of the characteristics of teaching resources. Finally, the cosine similarity method is used to calculate the similarity and interest of user attribute vectors, and the predicted interest of users in resources is obtained. According to the predicted interest value, the recommended list of cultural education online teaching resources is generated from high to low, and recommended results are obtained. The experimental results show that this method has a better effect on online teaching resources recommendation of Chinese education.

Keywords: cosine similarity; knowledge graph; TF-IDF method; resource recommendation; Chinese education.

DOI: 10.1504/IJBIDM.2024.137740

International Journal of Business Intelligence and Data Mining, 2024 Vol.24 No.3/4, pp.252 - 265

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

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