Tourist route customization method and system based on deep reinforcement learning

Abstract

The invention discloses a travel route customization method and system based on deep reinforcement learning. The method comprises the steps of mining historical preference scores of tourists according to hotel, scenic spot and traffic data; a route optimization framework based on a deep reinforcement learning algorithm; obtaining tourist demands, and generating an intelligent and customized route; the route is dynamically updated based on the real-time scene change of the tourist; according to the method, intelligent and customized routes including the hotels and the scenic spots can be quickly obtained, more diversified and convenient services are provided for tourists, and the time for the tourists to select the hotels and the scenic spots and plan the routes is saved; the environment is a tourism environment where tourists are located actually, the tourism environment comprises POI information and tourist input information, routes are generated according to historical preferences and demands of the tourists, and the design requirements of individuation and customization of the tourists can be met; according to the real tourism path of the tourist, the route is dynamically and intelligently planned, and the optimization model is further learned, so that the satisfaction and experience of the tourist can be improved.

Description

technical field [0001] The invention belongs to the field of travel route customization, and specifically relates to a method and system for customizing travel routes based on deep reinforcement learning. Background technique [0002] As an important part of the modern service industry, tourism has gradually become one of the most important economic driving forces in the world. With the popularity of tourism, the behavior of tourists has also undergone great changes, and tourists increasingly prefer "customized tours" and "self-drive tours" instead of pre-organized routes or standard travel packages. [0003] The customized tourist itinerary problem is called the "tourist itinerary design problem", and its purpose is to design tourist itineraries for tourists by maximizing their total preference score according to their constraints. Existing customized tour itineraries pay relatively little attention to hotel selection, which is, however, an important part of multi-day tour...

AI Technical Summary

Problems solved by technology

[0004] Existing mainstream methods are various heuristics, mainly focusing on selecting and ranking POIs, but ignoring the optimization of the sightseeing time spent on each POIs, and also ignoring the real traffic and real preferences of tourists for POIs

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