TY - GEN
T1 - Active learning for tag recommendation utilizing on-line photos lacking tags
AU - Gao, Yajun
AU - Li, Baoxin
PY - 2012
Y1 - 2012
N2 - Recommending text tags for on-line photos is useful for Internet photo services. Typical solutions to this problem require analysis of the correlation among different attributes of the photos, including the correlation between the textual features and visual features computed from a photo. However, most on-line photos have very few tags or even no tags, and thus they contribute little or none to the analysis of tag-photo correlation, which is a key component in those schemes that rely on such analysis for tag recommendation. To address this practical challenge, we propose an active learning method for incorporating photos with no or few tags so as to enhance the correlation analysis for improved performance in tag recommendation. We demonstrate the effectiveness of the proposed approach using a dataset of more than 33,000 photos collected from Flickr.
AB - Recommending text tags for on-line photos is useful for Internet photo services. Typical solutions to this problem require analysis of the correlation among different attributes of the photos, including the correlation between the textual features and visual features computed from a photo. However, most on-line photos have very few tags or even no tags, and thus they contribute little or none to the analysis of tag-photo correlation, which is a key component in those schemes that rely on such analysis for tag recommendation. To address this practical challenge, we propose an active learning method for incorporating photos with no or few tags so as to enhance the correlation analysis for improved performance in tag recommendation. We demonstrate the effectiveness of the proposed approach using a dataset of more than 33,000 photos collected from Flickr.
KW - Tag recommendation
KW - active learning
UR - http://www.scopus.com/inward/record.url?scp=84875857226&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84875857226&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2012.6467498
DO - 10.1109/ICIP.2012.6467498
M3 - Conference contribution
AN - SCOPUS:84875857226
SN - 9781467325332
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 2869
EP - 2872
BT - 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
T2 - 2012 19th IEEE International Conference on Image Processing, ICIP 2012
Y2 - 30 September 2012 through 3 October 2012
ER -