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.