document: Tag ranking Social media sharing web sites like Flickr allow users to annotate images with free tags , which significantly 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 first estimate initial relevance scores for the tags based on probability density estimation , and then perform a random walk over a tag similarity graph to refine 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 .
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