Title: An unstructured data retrieval method for English online course resources based on hash learning algorithm

Authors: Man He; Jin Xie

Addresses: School of Foreign Languages and Cultures, Geely University of China, Chengdu, 641423, China ' School of Foreign Languages and Cultures, Geely University of China, Chengdu, 641423, China

Abstract: The retrieval of unstructured data often suffers from low retrieval accuracy and inconsistent retrieval results. Therefore, this paper focuses on the research of unstructured data retrieval methods for English online course resources based on hash learning algorithm. Constructing an unstructured dataset of English online course resources and conducting preprocessing; construct a supervised identification matrix for unstructured data and perform dimensionality reduction on the unstructured data; using hash functions and tanh activation functions to obtain unstructured data feature binary hash codes; establish a hash learning algorithm data retrieval model, use the distance loss function of samples to calculate the similarity between hash codes, use keywords as tag information, and achieve the retrieval of unstructured data of English online course resources. Through experimental verification, the proposed method consistently achieves a retrieval consistency of over 90%, a retrieval recall rate of over 85%, high retrieval accuracy, and reliable retrieval results.

Keywords: unstructured data; data retrieval; hash learning; English online course resources; supervised discrimination projection.

DOI: 10.1504/IJITM.2025.151551

International Journal of Information Technology and Management, 2025 Vol.24 No.3/4, pp.222 - 236

Received: 05 Sep 2024
Accepted: 07 Feb 2025
Published online: 05 Feb 2026 *

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