Application of collaborative filtering algorithm based on time decay function in music teaching recommendation model.

ABSTRACT: To address the issues of data sparsity, scalability, and cold start in the traditional teaching resource recommendation process, this paper presents an enhanced collaborative filtering (CF) recommendation algorithm incorporating a time decay (TD) function. By aligning with the human memory forgetting curve, the TD function is employed as a weighting factor, enabling the calculation of similarity and user preferences constrained by the TD, thus amplifying the weight of user interest over a short period and achieving the integration of short-term and long-term interests. The results indicate that the RMSE of the proposed combined recommendation algorithm (TD-CF) is only 8.95 when the number of recommendations reaches 100, which is significantly lower than the comparison model, which exhibits

SUBMITTER: Zhao Y 

PROVIDER: S-EPMC11639207 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature