AI-driven dynamic trip generation mechanism
The core function of iMean AI adopts the dual-engine matching mode of demand and resources. On the demand side, the system extracts travel elements through semantic analysis: when the user inputs "7-day family trip from Beijing to Paris with a budget of 10,000 RMB", the AI automatically recognizes key parameters such as the destination, duration, type of people, cost constraints, etc. The platform accesses 300+ data sources such as Skyscanner in real time, and integrates mainstream hotels such as Booking.com. On the resource side, the platform has real-time access to flight information from 300+ data sources such as Skyscanner, integrates room data from mainstream hotels such as Booking.com, and obtains local service resources such as attraction tickets through cooperative suppliers. The matching process uses reinforcement learning algorithms, such as prioritizing the recommendation of kid-friendly hotels and queue-free attraction tickets for family users, and optimizing the commute time between the airport and the venue for business users. Tests show that the system generates trips with an average response time of 3.2 seconds and a user satisfaction rate of 89%.
This answer comes from the articleiMean AI: A one-stop personalized travel planning toolThe
English 
简体中文 
日本語 
Deutsch 
Português do Brasil