1. In a computing environment, a method comprising: receiving input comprising a tagged image collection, including a plurality of images with one or more associated text labels; identifying a first set of homogeneous relationships within the plurality of images to provide an image-to-image data structure, wherein the first set of homogeneous relationships represent pair-wise similarities between one or more images based on features of each image; identifying a second set of homogeneous relationships within words of the one or more associated text labels to provide a word-to-word data structure, wherein the second set of homogeneous relationships represent pair-wise similarities between the words of the one or more associated text labels; identifying a third set of heterogeneous relationships between the plurality of images and the words of the one or more associated text labels to provide an image-to-word data structure, wherein the third set of heterogeneous relationships define one or more associations between each of the plurality of images and each of the words of the one or more associated text labels; and processing the image-to-image data structure, the word-to-word data structure, and the image-to-word data structure simultaneously to identify both visual and textual exemplars for the tagged image collection and output at least one of a visual summary of the input or a textual summary of the input using the visual and textual exemplars.
1. In a computing environment, a method comprising: receiving input comprising a tagged image collection, including a plurality of images with one or more associated text labels; identifying a first set of homogeneous relationships within the plurality of images to provide an image-to-image data structure, wherein the first set of homogeneous relationships represent pair-wise similarities between one or more images based on features of each image; identifying a second set of homogeneous relationships within words of the one or more associated text labels to provide a word-to-word data structure, wherein the second set of homogeneous relationships represent pair-wise similarities between the words of the one or more associated text labels; identifying a third set of heterogeneous relationships between the plurality of images and the words of the one or more associated text labels to provide an image-to-word data structure, wherein the third set of heterogeneous relationships define one or more associations between each of the plurality of images and each of the words of the one or more associated text labels; and processing the image-to-image data structure, the word-to-word data structure, and the image-to-word data structure simultaneously to identify both visual and textual exemplars for the tagged image collection and output at least one of a visual summary of the input or a textual summary of the input using the visual and textual exemplars. 2. The method of claim 1 wherein finding the first set of relationships between images comprises selecting pairs of images, and determining a similarity for each selected pair based upon features extracted from each image.