Title :
Photo-Taking Point Recommendation with Nested Clustering
Author :
Kimura, K. ; Hung-Hsuan Huang ; Kawagoe, Kyoji
Author_Institution :
Ritsumeikan Univ., Kusatsu, Japan
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;
Conference_Titel :
Multimedia (ISM), 2012 IEEE International Symposium on
Conference_Location :
Irvine, CA
Print_ISBN :
978-1-4673-4370-1
DOI :
10.1109/ISM.2012.20