Using a bipartite graph to model and derive image and text associations

摘要

A method for deriving probabilistic association scores based on image content is provided. A bipartite graph is constructed based on a database of image content and associated textual content. One partition of the bipartite graph contains image content and the other partition of the bipartite graph contains textual content. Weighted edges between nodes in the two partitions represent associations between the image content and textual content in the database. Random walks on the bipartite graph are performed to derive probabilistic association scores between image content and textual content. Association scores are used to automatically annotate images and detect spurious image tags.