| Title |
Complementing Travel Itinerary Recommendation Using Location-Based Social Networks |
| ID_Doc |
15233 |
| Authors |
Zhou J.; Gu Y.; Lin W. |
| Year |
2019 |
| Published |
Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019 |
| DOI |
http://dx.doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00330 |
| Abstract |
We proposed in a previous work a recommendation system that, according to the requirements specified by its users, was capable of generating a few travel itineraries of distinct features (e.g. the most appealing itinerary, the shortest itinerary or the itinerary with the highest performance/price ratio) for user selection. We anticipated to complement the recommended travel itineraries by taking advantage of recent advances in location-acquisition and wireless communication technologies. With such technologies, people can share geo-spatial locations and location-based activities in the physical world via location-based social networks (LBSN), which makes it possible to help deduce a prospective traveler's dream destination using their check-ins published and shared on those websites. These user check-ins are informative in that a user's historical behaviors is a powerful indicator of his/her preferences. Therefore, we looked into and utilized user check-ins and social connections when building up a trip planner (such as our recommender) so as to better serve the travelers who may merely wander a travel website and seek the best vacation packages, flights, or hotel for their next trip. Our experiment verified the feasibility and efficiency of using user check-ins and social connections accessible from LBSNs in terms of discovering users' potential travel destination. © 2019 IEEE. |
| Author Keywords |
Itinerary recommendation; Location-based social networks; User clustering |
