Construction Of Tag Ontological Graphs By Locally Minimizing Weighted Average Hops

We present a data-driven approach for the construction of ontological graphs on a set of image tags obtained from annotated image corpus. We treat each tag as a node in a graph, and starting with a preliminary graph obtained using WordNet, we propose the graph construction as a refinement of the preliminary graph using corpus statistics. Towards this, we formulate an optimization problem which is solved using a local search based approach. To evaluate the constructed ontological graphs, we propose a novel task which involves associating test images with tags while observing partial set of associated tags.