Summarizing tourist destinations by mining user-generated travelogues and photos

  • Authors:

  • Yanwei Pang;Qiang Hao;Yuan Yuan;Tanji Hu;Rui Cai;Lei Zhang

  • Affiliations:

  • School of Electronic Information Engineering, Tianjin University, Tianjin 300072, PR China;School of Electronic Information Engineering, Tianjin University, Tianjin 300072, PR China;Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, ...;School of Electronic Information Engineering, Tianjin University, Tianjin 300072, PR China;Microsoft Research Asia, Beijing 100190, PR China;Microsoft Research Asia, Beijing 100190, PR China

  • Venue:
  • Computer Vision and Image Understanding
  • Year:
  • 2011

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Abstract

Automatically summarizing tourist destinations with both textual and visual descriptions is highly desired for online services such as travel planning, to facilitate users to understand the local characteristics of tourist destinations. Travelers are contributing a great deal of user-generated travelogues and photos on the Web, which contain abundant travel-related information and cover various aspects (e.g., landmarks, styles, activities) of most locations in the world. To leverage the collective knowledge of travelers for destination summarization, in this paper we propose a framework which discovers location-representative tags from travelogues and then select relevant and representative photos to visualize these tags. The learnt tags and selected photos are finally organized appropriately to provide an informative summary which describes a given destination both textually and visually. Experimental results based on a large collection of travelogues and photos show promising results on destination summarization.