A Survey of Recent Advances in Commonsense Knowledge Acquisition: Methods and Resources  

作　　者：Chenhao Wang Jiachun Li Yubo Chen Kang Liu Jun Zhao 

机构地区：[1]Laboratory of Cognition and Decision Intelligence for Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China [2]School of Artificial Intelligence,University of Chinese Academy of Sciences,Beijing 100049,China [3]Beijing Academy of Artificial Intelligence,Beijing 100049,China

出　　处：《Machine Intelligence Research》2025年第2期201-218,共18页机器智能研究(英文版)

基　　金：supported by the National Key Research and Development Program of China(No.2020AAA 0106400);the National Natural Science Foundation of China(Nos.61976211 and 62176257);supported by the Strategic Priority Research Program of Chinese Academy of Sciences,China(No.XDA27020100);the Youth Innovation Promotion Association CAS,China,and Yunnan Provincial Major Science and Technology Special Plan Projects,China(No.202202AD 080004).

摘　　要：Imparting human-like commonsense to machines is a long-term goal in the artificial intelligence community.To achieve this goal,constructing large-scale commonsense knowledge resources is an important step.In recent years,due to increasing demand,commonsense knowledge has become a rapidly growing research field,resulting in a surge of new acquisition methods and corresponding resources.These advances have empowered a variety of downstream AI tasks.However,constructing large-scale commonsense knowledge resources remains an ongoing and challenging task.It is still difficult to efficiently collect large-scale,high-quality commonsense knowledge.In this paper,we systematically review recent advances in commonsense knowledge acquisition methods and resources,providing a comprehensive summary of recent research scope,the characteristics of different resources,and unsolved challenges.

关 键 词：Commonsense knowledge knowledge acquisition knowledge representation and processing knowledge resource knowledge engineering. 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]