Web image co-clustering based on tag and image content fusion

Jie Chen,Jianlong Tan,Xiangzhou Yin,Hao Liao

Beijing（2010）

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摘要

In Web 2.0 applications, users always label digital images using textual descriptions, which are also called tags. As a result, a web image usually carries both tag and visual content information. In order to improve the retrieval performance of web images, in this paper, we propose an error-driven fusion co-clustering algorithm, which combines images' tags, visual contents together for analysis. Experimental results demonstrate that our algorithm outperforms other simple clustering methods.

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关键词

pattern clustering,image fusion,web 2.0,error-driven fusion co-clustering algorithm,error-driven fusion,retrieval performance,images' tags,image retrieval,internet,textual descriptions,image content fusion,web image co-clustering,visual content information,co-clustering,content-based retrieval,visualization,bipartite graph,co clustering,clustering algorithms,web 2 0,feature extraction,digital image,semantics

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