Functional Semantic Categories for Art History Text : Human Labeling and Preliminary Machine Learning


The CLiMB project investigates semi-automatic methods to extract descriptive metadata from texts for indexing digital image collections. We developed a set of functional semantic categories to classify text extracts that describe images. Each semantic category names a functional relation between an image depicting a work of art historical significance, and… (More)

1 Figure or Table


  • Presentations referencing similar topics