ContextRank: Personalized tourism recommendation by exploiting context information of geotaggedweb photos

Kai Jiang, Peng Wang, Nenghai Yu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Scopus citations

Abstract

In this paper, we propose a method: ContextRank, which utilizes the vast quantity of geotagged photos in photo sharing website to recommend travel locations. To enhance the personalized recommendation performance, our method exploits different context information of photos, such as textual tags, geotags, visual information, and user similarity. Context-Rank first detects landmarks from photos' GPS locations, and estimates the popularity of each landmark. Within each landmark, representative photos and tags are extracted. Furthermore, ContextRank calculates the user similarity based on users' travel history. When a user's geotagged photos are given, the landmark popularity, representative photos and tags, and the user similarity are used to predict the user preference of a landmark from different aspects. Finally a learning to rank algorithm is introduced to combine different preference predictions to give the final recommendation. Experiments performed on a dataset collected from Panoramio show that the ContextRank can obtain a better result than the state-of-the-art method.

Original languageEnglish
Title of host publicationProceedings - 6th International Conference on Image and Graphics, ICIG 2011
Pages931-937
Number of pages7
DOIs
StatePublished - 2011
Externally publishedYes
Event6th International Conference on Image and Graphics, ICIG 2011 - Hefei, Anhui, China
Duration: 12 Aug 201115 Aug 2011

Publication series

NameProceedings - 6th International Conference on Image and Graphics, ICIG 2011

Conference

Conference6th International Conference on Image and Graphics, ICIG 2011
Country/TerritoryChina
CityHefei, Anhui
Period12/08/1115/08/11

Keywords

  • Context information
  • Geotagged photos
  • Tourism recommendation

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