16. A processing system comprising: an image retrieval program (IRP) for querying a collection of digital images; a mining module in the IRP, the mining module to use local and global feature descriptors to automatically rank the collection of digital images with respect to similarity to a user-selected positive example, wherein each local feature descriptor represents a portion of an image based on a division of the image into multiple portions, and wherein each global feature descriptor represents an image as a whole; the mining module to use a final classifier and multiple different intermediate classifiers to perform the automatic ranking; the different intermediate classifiers to generate intermediate relevance metrics with respect to different modalities; the final classifier to blend results from the intermediate classifiers into a final relevance metric to be used for presenting the images from the collection in the user interface; after the final relevance metric is generated, the mining module to receive input identifying a second example image for use in querying the collection of digital images; the mining module to automatically determine at least one new intermediate classifier, based at least in part on the example image; the mining module to automatically determine a new final classifier, based at least in part on the example images; and the mining module to use the new intermediate classifier and the new final classifier to automatically re-rank the collection of digital images with respect to similarity to the example image.
16. A processing system comprising: an image retrieval program (IRP) for querying a collection of digital images; a mining module in the IRP, the mining module to use local and global feature descriptors to automatically rank the collection of digital images with respect to similarity to a user-selected positive example, wherein each local feature descriptor represents a portion of an image based on a division of the image into multiple portions, and wherein each global feature descriptor represents an image as a whole; the mining module to use a final classifier and multiple different intermediate classifiers to perform the automatic ranking; the different intermediate classifiers to generate intermediate relevance metrics with respect to different modalities; the final classifier to blend results from the intermediate classifiers into a final relevance metric to be used for presenting the images from the collection in the user interface; after the final relevance metric is generated, the mining module to receive input identifying a second example image for use in querying the collection of digital images; the mining module to automatically determine at least one new intermediate classifier, based at least in part on the example image; the mining module to automatically determine a new final classifier, based at least in part on the example images; and the mining module to use the new intermediate classifier and the new final classifier to automatically re-rank the collection of digital images with respect to similarity to the example image. 23. A processing system according to claim 16 , further comprising: multiple processing units; and a machine-accessible medium responsive to the multiple processing units, the machine-accessible medium comprising the image retrieval program.