9. A computer program product embodied in a computer readable storage medium for efficiently identifying images, videos, audio files or documents relevant to a user using attribute binary trees for guiding relevance feedback, the computer program product comprising the programming instructions for: constructing a binary search tree for each relative attribute of interest in a pool of database images, videos, audio files or documents; setting a current pivot exemplar for each binary tree as corresponding to a database image, video, audio file or document with a median relative attribute value among all remaining database items in a subtree; predicting an information gain that would result from asking a user how a user's target image, video, audio file or document compares to each pivot exemplar of a plurality of pivot exemplars, wherein said comparison is made in terms of an attribute associated with that pivot's binary tree; providing a pivot exemplar deemed most informative from among said plurality of pivot exemplars to a user to provide a comparison between said attribute in said user's target image, video, audio file or document and in said current pivot exemplar; and receiving comparative attribute feedback from said user regarding whether a degree of said attribute in said user's target image, video, audio file or document is more, less or equal with said attribute displayed in said provided pivot exemplar.
9. A computer program product embodied in a computer readable storage medium for efficiently identifying images, videos, audio files or documents relevant to a user using attribute binary trees for guiding relevance feedback, the computer program product comprising the programming instructions for: constructing a binary search tree for each relative attribute of interest in a pool of database images, videos, audio files or documents; setting a current pivot exemplar for each binary tree as corresponding to a database image, video, audio file or document with a median relative attribute value among all remaining database items in a subtree; predicting an information gain that would result from asking a user how a user's target image, video, audio file or document compares to each pivot exemplar of a plurality of pivot exemplars, wherein said comparison is made in terms of an attribute associated with that pivot's binary tree; providing a pivot exemplar deemed most informative from among said plurality of pivot exemplars to a user to provide a comparison between said attribute in said user's target image, video, audio file or document and in said current pivot exemplar; and receiving comparative attribute feedback from said user regarding whether a degree of said attribute in said user's target image, video, audio file or document is more, less or equal with said attribute displayed in said provided pivot exemplar. 10. The computer program product as recited in claim 9 further comprising the programming instructions for: updating relevance predictions on said pool of database images, videos, audio files or documents in response to receiving said comparative attribute feedback.