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SocialTrail:Recommending Social Trajectories from Location-Based Social Networks

  • Qinzhe ZhangEmail author
  • Litao Yu
  • Guodong Long
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9093)

Abstract

Trajectory recommendation plays an important role for travel planning. Most existing systems are mainly designed for spot recommendation without the understanding of the overall trip and tend to utilize homogeneous data only (e.g., geo-tagged images). Furthermore, they focus on the popularity of locations and fail to consider other important factors like traveling time and sequence, etc. In this paper, we propose a novel system that can not only integrate geo-tagged images and check-in data to discover meaningful social trajectories to enrich the travel information, but also take both temporal and spatial factors into consideration to make trajectory recommendation more accurately.

Keywords

Tourist Attraction Recommendation Algorithm Social Data Travel Information Social Media User 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Arase, Y., Xie, X., Hara, T., Nishio, S.: Mining people’s trips from large scale geo-tagged photos. In: ACM MM (2010)Google Scholar
  2. 2.
    Cheng, A.-J., Chen, Y.-Y., Huang, Y.-T., Hsu, W.H., Mark Liao, H.-Y.: Personalized travel recommendation by mining people attributes from community-contributed photos. In: ACM MM (2011)Google Scholar
  3. 3.
    Liu, J., Huang, Z., Chen, L., Shen, H.T., Yan, Z.: Discovering areas of interest with geo-tagged images and check-ins. In: ACM MM (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.The University of QueenslandBrisbaneAustralia
  2. 2.The University of Technology SydneyUltimoAustralia

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