E-learning recommendation framework based on deep learning
Xiao Wang, Yuanyuan Zhang, Shengnan Yu, Xiwei Liu, Yong Yuan, Fei–Yue Wang · 2017
In the paper, considering the limitation of effective method in E-learning area, a recommendation framework for E-Learning based on deep learning is proposed. Our model is based on deep learning, which has strong capability to learn from large-scale data. It has some improvements than previous methods. First, it is based on the conventional K-Nearnest Neighbor(KNN) method to train a model, thus its accuracy is guaranteed. Second, it can recommend the new item whose similarity can not be calculated. Third, it greatly reduces the heavy burden for a running system, which is useful in real practice of recommendation systems. In conclusion, the proposed framework can offer a new recommendation method for more personlized learning in the future.