The disclosed subject matter improves iterative results of content-based image
retrieval (CBIR) using a bigram model to correlate relevance feedback. Specifically,
multiple images are received responsive to multiple image search sessions. Relevance
feedback is used to determine whether the received images are semantically relevant.
A respective semantic correlation between each of at least one pair of the images
is then estimated using respective bigram frequencies. The bigram frequencies are
based on multiple search sessions in which each image of a pair of images is semantically relevant.
