Summarizing tourist destinations by mining user-generated travelogues and photos

Yanwei Pang, Qiang Hao, Yuan Yuan, Tanji Hu, Rui Cai, Lei Zhang

Research output: Contribution to journalArticlepeer-review

86 Scopus citations

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.

Original languageEnglish
Pages (from-to)352-363
Number of pages12
JournalComputer Vision and Image Understanding
Volume115
Issue number3
DOIs
StatePublished - Mar 2011
Externally publishedYes

Keywords

  • Destination summarization
  • Travelogue mining
  • User-generated content
  • Virtual tour

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