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Web mining for web image retrieval
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Probabilistic multimedia retrieval
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MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
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WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
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IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
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ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
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ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
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IEEE Transactions on Circuits and Systems for Video Technology
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In this paper, we propose an iterative similarity propagation approach to explore the inter-relationships between Web images and their textual annotations for image retrieval. By considering Web images as one type of objects, their surrounding texts as another type, and constructing the links structure between them via webpage analysis, we can iteratively reinforce the similarities between images. The basic idea is that if two objects of the same type are both related to one object of another type, these two objects are similar; likewise, if two objects of the same type are related to two different, but similar objects of another type, then to some extent, these two objects are also similar. The goal of our method is to fully exploit the mutual reinforcement between images and their textual annotations. Our experiments based on 10,628 images crawled from the Web show that our proposed approach can significantly improve Web image retrieval performance.