Modern technology enables organizations to build large-scale data repositories. The utility of such repositories, however, is limited if they don't support flexible methods of extracting knowledge, especially for repositories of visual artifacts. Existing content-based visual media retrieval systems create models that are often optimized to the domain knowledge provided by experts during training processes. However, most of these systems lack the flexibility to address the gap between computer and human representations of visual patterns.