Constructing a personalized travel itinerary recommender system with the Internet of Things.

With the rapid development of Internet and the application of smart phone, the percentage of people who choose self-guide tour increased significantly. Also, with the expectation of reaching 57 billion smart connected devices by 2025, the application of Internet of Things (IoT) has spread widely. Using IoT technology to support the development of recommender system has become a widely studied topic. To elevate the quality of self-guided tours and reduce the time costs associated with arranging them, this paper proposes a system that recommends self-guided tour services according to users' personal preferences and professionals' travel recommendations in the IoT environment. This system automatically generates travel itineraries after users input some basic information. Prior to generating itineraries, this system references travel itinerary recommendations retrieved from a travel itinerary database (developed by professionals) as well as users' personal preferences and trip constraints. Next, it produces travel itinerary recommendations. Users can modify the travel itinerary recommendations of the proposed system according to their individual needs, and this system uses the branch-and-bound algorithm to assemble modified points of interest to produce optimal travel itineraries. [ABSTRACT FROM AUTHOR]