Proceedings of the 18th international conference on World wide web
NUS-WIDE: a real-world web image database from National University of Singapore
Proceedings of the ACM International Conference on Image and Video Retrieval
Image tag re-ranking by coupled probability transition
Proceedings of the 20th ACM international conference on Multimedia
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In this paper, we propose to explore the relevance between tags for image tag re-ranking. The key component is to define a global tag-tag similarity matrix, which is achieved by analysis in both semantic and visual aspects. The text semantic relevance is explored by the Latent Semantic Indexing (LSI) model [1].For the visual information, the tag-relevance can be propagated by reconstructing exemplar images with visually and semantically consistent images. Based on our tag relevance matrix, a random-walk approach is leveraged to discover the significance of each tag. Finally, all tags in an image are re-ranked by their significance values. Extensive experiments show its effectiveness on an image dataset with a large tags vocabulary.