论文标题
零拍学习的本体学指导语义组成
Ontology-guided Semantic Composition for Zero-Shot Learning
论文作者
论文摘要
零射击学习（ZSL）是一个流行的研究问题，旨在通过利用与某些附带信息的阶层间关系来预测那些从未出现过培训阶段的课程。在这项研究中，我们建议通过OWL（Web Ondology语言）本体论对班级标签的组成和表达语义进行建模，并进一步开发带有本体嵌入的新ZSL框架。关于动物图像分类和视觉问题答案的一些主要实验已经验证了该有效性。
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.
