  Zero-shot learning (ZSL) which aims at predicting classes that have never
appeared during the training using external knowledge (a.k.a. side information)
has been widely investigated. In this paper we present a literature review
towards ZSL in the perspective of external knowledge, where we categorize the
external knowledge, review their methods and compare different external
knowledge. With the literature review, we further discuss and outlook the role
of symbolic knowledge in addressing ZSL and other machine learning sample
shortage issues.
