TY  - CONF
ID  - www200936
UR  - http://www2009.eprints.org/36/
A1  - Liu, Dong
A1  - Hua, Xian-Sheng
A1  - Yang, Linjun
A1  - Wang, Meng
A1  - Zhang, Hong-Jiang
Y1  - 2009/04//
N2  - Social media sharing web sites like Flickr allow users to annotate images with free tags, which signi?cantly facilitate Web image search and organization. However, the tags associated with an image generally are in a random order without any importance or relevance information, which limits the effectiveness of these tags in search and other applications. In this paper, we propose a tag ranking scheme, aiming to automatically rank the tags associated with a given image according to their relevance to the image content. We ?rst estimate initial relevance scores for the tags based on probability density estimation, and then perform a random walk over a tag similarity graph to re?ne the relevance scores. Experimental results on a 50, 000 Flickr photo collection show that the proposed tag ranking method is both effective and efficient. We also apply tag ranking into three applications: (1) tag-based image search, (2) tag recommendation, and (3) group recommendation, which demonstrates that the proposed tag ranking approach really boosts the performances of social-tagging related applications.
TI  - Tag Ranking
SP  - 351
M2  - Madrid, Spain
AV  - public
EP  - 351
T2  - 18th International World Wide Web Conference
ER  -