  Zero-shot learning (ZSL) is a popular research problem that aims at
predicting for those classes that have never appeared in the training stage by
utilizing the inter-class relationship with some side information. In this
study, we propose to model the compositional and expressive semantics of class
labels by an OWL (Web Ontology Language) ontology, and further develop a new
ZSL framework with ontology embedding. The effectiveness has been verified by
some primary experiments on animal image classification and visual question
answering.
