The application discloses a hub AI travel small assistant working method based on multi-
modal fusion and MaaS cooperation, which comprises the following steps: 1, collecting the demand of a user through a man-
machine interaction interface, understanding the intention of the user through a
natural language processing (NLP) module, and using a service arrangement engine to disassemble the demand of the user into several sub-services; 2, collecting the individual preference of the user according to all the sub-services; 3, automatically calling internal
algorithm modules and external
service provider interfaces in logical order; 4, using an AI
large model to perform fusion analysis on multi-dimensional data obtained by using the internal
algorithm modules and the external
service provider interfaces, calculating the comprehensive utility of each travel scheme in real time, and performing sorting and recommendation; the sorting and recommendation is a recommended travel
service mode combined with the individual preference; 5, realizing the corresponding sub-service through the external
service provider interface. The application solves the fundamental contradiction between service fragmentation and demand diversification.