Tag ranking Export

@inproceedings{citeulike:4490956, abstract = {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}, address = {New York, NY, USA}, author = {Liu, Dong and Hua, Xian S. and Yang, Linjun and Wang, Meng and Zhang, Hong J.}, booktitle = {WWW '09: Proceedings of the 18th international conference on World wide web}, citeulike-article-id = {4490956}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1526757}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1526709.1526757}, comment = {For image on flickr. Compute relevance by (1)co-tagged image similarity and (2) random walk on tags in the image. In (2) the graph edge weight is defined by content similarity and co-occurrence. Evaluate by IR method, image is query, ordered tags are search results. }, doi = {10.1145/1526709.1526757}, isbn = {978-1-60558-487-4}, keywords = {auto-tagging, social-tagging}, location = {Madrid, Spain}, pages = {351--360}, posted-at = {2009-05-08 03:17:29}, priority = {2}, publisher = {ACM}, title = {Tag ranking}, url = {http://dx.doi.org/10.1145/1526709.1526757}, year = {2009} }

TY - CONF ID - citeulike:4490956 L3 - citeulike-article-id:4490956 N2 - 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 CY - Madrid, Spain SN - 978-1-60558-487-4 AD - New York, NY, USA EP - 360 TI - Tag ranking PB - ACM T2 - WWW '09: Proceedings of the 18th international conference on World wide web SP - 351 KW - auto-tagging KW - social-tagging N1 - For image on flickr. Compute relevance by (1)co-tagged image similarity and (2) random walk on tags in the image. In (2) the graph edge weight is defined by content similarity and co-occurrence. Evaluate by IR method, image is query, ordered tags are search results. AU - Liu, Dong AU - Hua, Xian AU - Yang, Linjun AU - Wang, Meng AU - Zhang, Hong PY - 2009/// UR - http://dx.doi.org/10.1145/1526709.1526757 ER -