Research on personalized recommendation of teaching resources based on joint probability matrix decomposition model and CNN improvement algorithm

Research on personalized recommendation of teaching resources based on joint probability matrix decomposition model and CNN improvement algorithm

This study proposes a teaching resource recommendation method (TRRDLMF) based on deep learning and probabilistic matrix decomposition, aiming to improve teaching resource recommendation’s accuracy and personalization level. The study combines hybrid neural network feature extraction of teaching reso...

Full description

Bibliographic Details
Main Authors: Ma Junxia, Liu Qilin, Zhang Zhifeng, Gu Peipei
Format: Article
Language:English
Published: Sciendo 2024-01-01
Series:Applied Mathematics and Nonlinear Sciences
Subjects:
deep learning
probability matrix decomposition
feature extraction
similarity
teaching resources recommendation
97m50
Online Access:https://doi.org/10.2478/amns-2024-0543

Internet

https://doi.org/10.2478/amns-2024-0543

Similar Items