Please use this identifier to cite or link to this item: https://doi.org/10.3969/j.issn.0253-2778.2011.02.003
Title: Automatic image tag ranking scheme based on visual content semantic relatedness
Authors: Zhao, Y.
Zha, Z. 
Li, S.
Wu, X.
Keywords: Content-relatedness
Flickr
Tag ranking
Visual content
Issue Date: 2011
Source: Zhao, Y.,Zha, Z.,Li, S.,Wu, X. (2011). Automatic image tag ranking scheme based on visual content semantic relatedness. Journal of University of Science and Technology of China 41 (2) : 108-115. ScholarBank@NUS Repository. https://doi.org/10.3969/j.issn.0253-2778.2011.02.003
Abstract: An automatic image tag ranking scheme was proposed based on visual content semantic relatedness, which sorted the tags of the community-contributed images according to the semantic relatedness between tags and image contents. Firstly, the semantic relatedness calculation between tag and image content was formulated as a probabilistic problem based on Bayes' theorem. Then, multiple visual features were fused to obtain reasonable probability evaluation for tag-image content relatedness in different semantic themes. This method has high scalability. Extensive experiments were conducted over a dataset consisting of 149 915 images downloaded from Flickr and experimental results demonstrate the effectiveness of the proposed method.
Source Title: Journal of University of Science and Technology of China
URI: http://scholarbank.nus.edu.sg/handle/10635/77823
ISSN: 02532778
DOI: 10.3969/j.issn.0253-2778.2011.02.003
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