Personalized movie recommendation in IoT-enhanced systems using graph convolutional network and multi-layer perceptron.

ABSTRACT: Exploring the optimization of communication strategies for animation films in the context of cross-cultural communication, this research integrates the Internet of Things (IoT) and convolutional networks. The research constructs a collaborative filtering (CF) movie recommendation model based on a graph convolutional neural network (GCN) and investigates its application in cross-cultural communication. The fusion of IoT and convolutional networks in movie communication is also analyzed, and the effectiveness of the proposed GCN-CF model is validated through comparative experiments. The results indicate that, compared to other models, the GCN-CF model achieves the lowest Root Mean Square Error (RMSE) on the MovieLens 100 K and MovieLens 1 M datasets, with values of 0.8762 and 0.8275, respect

SUBMITTER: Ye S 

PROVIDER: S-EPMC11502693 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature