• DocumentCode
    3139508
  • Title

    Photo-Taking Point Recommendation with Nested Clustering

  • Author

    Kimura, K. ; Hung-Hsuan Huang ; Kawagoe, Kyoji

  • Author_Institution
    Ritsumeikan Univ., Kusatsu, Japan
  • fYear
    2012
  • fDate
    10-12 Dec. 2012
  • Firstpage
    65
  • Lastpage
    68
  • Abstract
    In this paper, we propose a novel recommendation method for photo-taking points from a large amount of social community photo collections. There are many research activities on photo-related recommendations from a lot of photos stored and managed by photo sharing web services, such as Flickr, Picas a and Panoramio, Although some methods, such as landmark recommendation, tag recommendation and photo recommendation have already been proposed, no photo-taking point recommendation methods have been realized yet for social photo collections. In order to realize photo-taking point recommendation, we introduce a novel point and photo selection method based on nested clustering. From our experiments, it is shown that better recommendation accuracy with our proposed method can be attained.
  • Keywords
    Web services; recommender systems; Flickr; Panoramio; Picasa; landmark recommendation; nested clustering; photo related recommendation; photo selection method; photo sharing Web services; photo taking point recommendation method; recommendation accuracy; social community photo collection; social photo collection; tag recommendation; Accuracy; Clustering methods; Communities; Feature extraction; Reliability; Smart phones; Vectors; Clustering; Photo sharing; Recommendation; Web service;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia (ISM), 2012 IEEE International Symposium on
  • Conference_Location
    Irvine, CA
  • Print_ISBN
    978-1-4673-4370-1
  • Type

    conf

  • DOI
    10.1109/ISM.2012.20
  • Filename
    6424632