Editorial for Special Issue on Commonsense Knowledge and Reasoning: Representation, Acquisition and Applications

doi:10.1007/s11633-024-1397-4

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	Editorial for Special Issue on Commonsense Knowledge and Reasoning: Representation, Acquisition and Applications
	Kang Liu 3; Yangqiu Song 2; Jeff Z. Pan 1
刊名	Machine Intelligence Research
	2024
卷号	21 期号:2 页码:215-216
ISSN号	2731-538X
DOI	10.1007/s11633-024-1397-4
英文摘要	Commonsense knowledge is an important resource for humans to understand the meanings or semantics of the data. The ability to learn and own commonsense knowledge is one of the major gaps between humans and machines. Although recent research progresses about deep learning, like Transformer, pre-trained models, etc., have made amazing breakthroughs in many fields, including computer version, natural language learning, etc., letting the machines have rich commonsense knowledge and possess the reasoning ability is still difficult and under-resolved. So far researchers continue to focus on building large-scale knowledge bases, such as WordNet, Freebase, ConceptNet, BabelNet, which include different knowledge types, such as concepts, entities, relations, events, and frames. However, they only build a few parts of commonsense knowledge types and cover limited scenarios. Considering these issues, the AI community has made recent efforts to build commonsense knowledge bases through different ways, including symbolic knowledge graphs and large language models. The focused and difficult problems include how to define and represent commonsense knowledge, how to acquire and learn commonsense knowledge, how to perform reasoning based on commonsense knowledge, how to apply commonsense knowledge for downstream applications, and so on.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/56034]
专题	自动化研究所_学术期刊_International Journal of Automation and Computing
作者单位	1.The University of Edinburgh, UK 2.Hongkong University of Science and Technology, China 3.Institute of Automation, Chinese Academy of Sciences, China
推荐引用方式 GB/T 7714	Kang Liu,Yangqiu Song,Jeff Z. Pan. Editorial for Special Issue on Commonsense Knowledge and Reasoning: Representation, Acquisition and Applications[J]. Machine Intelligence Research,2024,21(2):215-216.
APA	Kang Liu,Yangqiu Song,&Jeff Z. Pan.(2024).Editorial for Special Issue on Commonsense Knowledge and Reasoning: Representation, Acquisition and Applications.Machine Intelligence Research,21(2),215-216.
MLA	Kang Liu,et al."Editorial for Special Issue on Commonsense Knowledge and Reasoning: Representation, Acquisition and Applications".Machine Intelligence Research 21.2(2024):215-216.