Intelligent Information Pushing and Induction for Hub Travelers Based on User Profiling Technology

Relying on big data technology, a hub traveler user profiling system is constructed, and a typical user priority filtering recommendation algorithm is proposed to determine the type of target users and travel preferences, and customize the push information based on different scenarios. In the multi-modal urban transportation network topology model, hyper-network theory and network extension technology are introduced to construct a multi-modal road network model oriented to big data of transportation hubs, and an improved A* algorithm is proposed to search for the optimal paths, on the basis of which, dynamic optimization is carried out for the travel chain based on the operating conditions of the transportation system, and the content of the travel chain information is determined to be pushed.