Personalized Travel Package With Multi-Point-of-Interest Recommendation Based on Crowdsourced User Footprints

  title={Personalized Travel Package With Multi-Point-of-Interest Recommendation Based on Crowdsourced User Footprints},
  author={Z. Yu and H. Xu and Zhe Yang and Bin Guo},
  journal={IEEE Transactions on Human-Machine Systems},
  • Z. Yu, H. Xu, +1 author Bin Guo
  • Published 2016
  • Computer Science
  • IEEE Transactions on Human-Machine Systems
  • Location-based social networks (LBSNs) provide people with an interface to share their locations and write reviews about interesting places of attraction. [...] Key Method The approach utilizes data collected from LBSNs to model users and locations, and it determines users' preferred destinations using collaborative filtering approaches. Recommendations are generated by jointly considering user preference and spatiotemporal constraints.Expand Abstract
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