Knowledge-aware Zero-Shot Learning: Survey and Perspective

Jiaoyan Chen; Yuxia Geng; Zhuo Chen; Ian Horrocks; Jeff Z. Pan; Huajun Chen

IJCAI 2021poster80 citations

Knowledge-aware Zero-Shot Learning: Survey and Perspective

Jiaoyan Chen, Yuxia Geng, Zhuo Chen, Ian Horrocks, Jeff Z. Pan, Huajun Chen

Abstract

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.

Knowledge representation and reasoning: GeneralMachine learning: GeneralMultidisciplinary topics and applications: General

BibTeX

@inproceedings{ijcai2021p597,
  title     = {Knowledge-aware Zero-Shot Learning: Survey and Perspective},
  author    = {Chen, Jiaoyan and Geng, Yuxia and Chen, Zhuo and Horrocks, Ian and Z. Pan, Jeff and Chen, Huajun},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Zhi-Hua Zhou},
  pages     = {4366--4373},
  year      = {2021},
  month     = {8},
  note      = {Survey Track},
  doi       = {10.24963/ijcai.2021/597},
  url       = {https://doi.org/10.24963/ijcai.2021/597},
}