Enhanced Collaborative Filtering Algorithm for Recommending Innovative Educational Resources in Higher Education Institutions
Year: 2024
Type: conference-paper
Abstract: This paper introduces a new method for efficiently recommending educational resources based on an enhanced collaborative filtering algorithm (ECFA). First, this algorithm calculates the similarities of educational resources to cluster them, and then assesses users' ratings of educational resources in higher education institutions based on the clustering results; finally, a list of innovative educational resources is created based on the rate to enhance the educational resource recommendations. The experimental results show that the proposed algorithm converges quickly, indicating its high efficiency in generating recommendations. Moreover, the method achieves a low Mean Absolute Error (MAE) when recommending innovative educational resources for higher education institutions, suggesting high quality.
Authors: Yue Wang, Jing Gao
Institution: Guilin University of Electronic Technology
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Funder: Division of Graduate Education
OpenAlex ID: W4412524827