Machine Intelligence Research (MIR)专题"Commonsense Knowledge and Reasoning: Representation, Acquisition and Applications"现公开征集原创稿件，截稿日期为2022年10月31日。专题客座编委：中科院自动化所刘康研究员、香港科技大学宋阳秋教授、爱丁堡大学Jeff Z. Pan (潘志明)教授。欢迎赐稿！

Machine Intelligence Research (ISSN 2731-538X) seeks original manuscripts for a special issue on "Commonsense Knowledge and Reasoning: Representation, Acquisition and Applications".

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 progress about deep learning, like Transformer, Pre-trained models, etc., has made amazing breakthroughs in many fields, including computer version, natural language learning, etc., letting the statistical models have the 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, like WordNet, Freebase, ConceptNet, BabelNet, etc., which describe multiple 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, although some of them have collected billions of instances. Considering these issues, the AI community has made recent efforts on building commonsense knowledge bases. 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.

​This special issue seeks original and novel contributions towards advancing the theory, methods, and applications for commonsense knowledge and reasoning. The special issue will provide a timely collection of recent advances to benefit the researchers and practitioners working in the broad research field of natural language processing, database, semantic web, and machine intelligence.

Topics of interest include (but are not limited to):

- The representation of commonsense knowledge

- Construction of commonsense knowledge bases

  - Complex concepts (such as negated concepts) in commonsense knowledge bases

- Pre-training models and commonsense knowledge bases

- Knowledge integration and linking

- Reasoning over commonsense knowledge

- Commonsense knowledge for  natural language inference

- Commonsense knowledge related applications including question answering, conversation, information retrieval, machine translations, etc.

​截稿日期：2022年10月31日

投稿地址（已开通）：

https://mc03.manuscriptcentral.com/mir

投稿时，请在系统中选择：

“Step 6 Details & Comments: Special Issue and Special Section”---“Special Issue on Commonsense Knowledge and Reasoning: Representation, Acquisition and Applications"

Prof. Kang Liu, Institute of Automation, Chinese Academy of Sciences, China (kliu@nlpr.ia.ac.cn)

Prof. Yangqiu Song, Hong Kong University of Science and Technology, Hong Kong (yqsong@cse.ust.hk) 

Prof. Jeff Z. Pan, The University of Edinburgh, United Kingdom (j.z.pan@ed.ac.uk)