NeTra: a toolbox for navigating large image databases
Multimedia Systems - Special issue on video content based retrieval
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual metrics for image database navigation
Perceptual metrics for image database navigation
Affinity rank: a new scheme for efficient web search
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Hierarchical clustering of WWW image search results using visual, textual and link information
Proceedings of the 12th annual ACM international conference on Multimedia
Video search reranking through random walk over document-level context graph
Proceedings of the 15th international conference on Multimedia
Visual ContextRank for web image re-ranking
LS-MMRM '09 Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining
Multimodal ranking for image search on community databases
Proceedings of the international conference on Multimedia information retrieval
Graph-based methods for the automatic annotation and retrieval of art prints
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Fast shape re-ranking with neighborhood induced similarity measure
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Leveraging community metadata for multimodal image ranking
Multimedia Tools and Applications
Ranking in heterogeneous social media
Proceedings of the 7th ACM international conference on Web search and data mining
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Drawing on the correspondence between spectral clustering, spectral dimensionality reduction, and the connections to the Markov chain theory, we present a novel unified framework for structural analysis of image database using spectral techniques. The framework provides a computationally efficient approach to both clustering and dimensionality reduction, or 2-D visualization. Within this framework, we can also infer the semantic degrees of the images, i.e. imagerank, which characterize the richness of semantics contained in the images. Some illustrative examples are discussed.