Tag-based social image search with visual-text joint hypergraph learning
Tag-based social image search has attracted great interest and how to order the search results based on relevance level is a research problem. Visual content of images and tags have both been investigated. However, existing methods usually employ tags and visual content separately or sequentially to...
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sg-smu-ink.sis_research-24462017-03-23T04:12:13Z Tag-based social image search with visual-text joint hypergraph learning GAO, Yue WANG, Meng LUAN, Huanboo SHEN, Jialie YAN, Shuicheng TAO, Dacheng Tag-based social image search has attracted great interest and how to order the search results based on relevance level is a research problem. Visual content of images and tags have both been investigated. However, existing methods usually employ tags and visual content separately or sequentially to learn the image relevance. This paper proposes a tag-based image search with visual-text joint hypergraph learning. We simultaneously investigate the bag-of-words and bag-of-visual-words representations of images and accomplish the relevance estimation with a hypergraph learning approach. Each textual or visual word generates a hyperedge in the constructed hypergraph. We conduct experiments with a real-world data set and experimental results demonstrate the effectiveness of our approach. 2011-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1447 info:doi/10.1145/2072298.2072054 https://ink.library.smu.edu.sg/context/sis_research/article/2446/viewcontent/TagBasedSocialImageSearch_2011.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University hypergraph learning tag-based image search visual-text Databases and Information Systems |
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hypergraph learning tag-based image search visual-text Databases and Information Systems GAO, Yue WANG, Meng LUAN, Huanboo SHEN, Jialie YAN, Shuicheng TAO, Dacheng Tag-based social image search with visual-text joint hypergraph learning |
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Tag-based social image search has attracted great interest and how to order the search results based on relevance level is a research problem. Visual content of images and tags have both been investigated. However, existing methods usually employ tags and visual content separately or sequentially to learn the image relevance. This paper proposes a tag-based image search with visual-text joint hypergraph learning. We simultaneously investigate the bag-of-words and bag-of-visual-words representations of images and accomplish the relevance estimation with a hypergraph learning approach. Each textual or visual word generates a hyperedge in the constructed hypergraph. We conduct experiments with a real-world data set and experimental results demonstrate the effectiveness of our approach. |
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text |
author |
GAO, Yue WANG, Meng LUAN, Huanboo SHEN, Jialie YAN, Shuicheng TAO, Dacheng |
author_facet |
GAO, Yue WANG, Meng LUAN, Huanboo SHEN, Jialie YAN, Shuicheng TAO, Dacheng |
author_sort |
GAO, Yue |
title |
Tag-based social image search with visual-text joint hypergraph learning |
title_short |
Tag-based social image search with visual-text joint hypergraph learning |
title_full |
Tag-based social image search with visual-text joint hypergraph learning |
title_fullStr |
Tag-based social image search with visual-text joint hypergraph learning |
title_full_unstemmed |
Tag-based social image search with visual-text joint hypergraph learning |
title_sort |
tag-based social image search with visual-text joint hypergraph learning |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2011 |
url |
https://ink.library.smu.edu.sg/sis_research/1447 https://ink.library.smu.edu.sg/context/sis_research/article/2446/viewcontent/TagBasedSocialImageSearch_2011.pdf |
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