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|Title:||Automatic image tag ranking scheme based on visual content semantic relatedness|
|Citation:||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|
|Appears in Collections:||Staff Publications|
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