This invention relates to the fields of intelligent transportation and
information processing technology, specifically a multimodal travel
route recommendation
system for passengers based on knowledge graphs and
machine learning. Deployed on a distributed
cloud computing architecture, the
system comprises a multi-source heterogeneous
data acquisition and preprocessing layer, a travel
knowledge graph construction and management layer, a dynamic spatiotemporal semantic
perception layer, a knowledge-guided deep recommendation decision layer, and an interactive
route presentation and feedback layer. These
layers are interconnected through a high-speed communication protocol to achieve closed-loop linkage. The
system integrates static traffic, real-time operations, passenger attributes, geographical environment, and unstructured text data to construct a semantically rich travel
knowledge graph, and combines graph
convolution and
temporal models to perceive the travel context. The recommendation engine, based on a multi-task neural network, completes
route generation, personalized
ranking, and interpretive reasoning. The system supports
interactive feedback and dynamic optimization, making it suitable for intelligent transportation and personalized travel services.