Knowledge Graph Driven Recommendation System Algorithm

In this paper, we propose a novel graph neural network-based recommendation model called KGLN, which leverages Knowledge Graph (KG) information to enhance the accuracy and effectiveness of personalized recommendations. We first use a single-layer neural network to merge individual node features in the graph, and then adjust the aggregation weights of neighboring entities by incorporating influence factors. The model evolves from a single layer to multiple layers through iteration, enabling entities to access extensive multi-order associated entity information. The final …

accuracy aggregation algorithm cs.cl cs.ir features graph graph neural network information knowledge knowledge graph layer merge network neural network node novel paper personalized personalized recommendations recommendation recommendation model recommendations