Title: Semantic retrieval method for learning resources in educational forms based on feedback algorithm

Authors: Zhiheng Liu

Addresses: Luoyang Vocational College of Culture and Tourism, Luoyang, Henan, China

Abstract: To improve the accuracy of resource retrieval methods and shorten retrieval time, the paper proposes a semantic retrieval method for learning resources in educational forms based on feedback algorithms. Firstly, design a learning resource corpus in the form of education, calculate the weights of key informational anchors, and use Latent Semantic Analysis (LSA) to perform Singular Value Decomposition (SVD) on the knowledge base matrix to obtain the semantic index of learning resources. Then, use implicit feedback information to calculate confidence and obtain semantic information of learning resources. Finally, determine the index weights, use the feedback mechanism of knowledge to adjust the search results, and complete the feedback update of the search results. The results show that the accuracy of the method proposed in this paper can reach 99.9%, with a time variation of 3.2-5.6 seconds, high retrieval efficiency and strong anti-interference ability.

Keywords: feedback algorithm; learning resources; natural language processing; educational form; implicit feedback information; keyword weight.

DOI: 10.1504/IJCAT.2024.146129

International Journal of Computer Applications in Technology, 2024 Vol.75 No.2/3/4, pp.73 - 80

Received: 06 Jun 2024
Accepted: 26 Sep 2024
Published online: 07 May 2025 *

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