Multi-Source Knowledge Reasoning Graph Network for Multi-Modal Commonsense Inference

doi:10.1145/3573201

CORC > 自动化研究所 > 中国科学院自动化研究所 > 多模态人工智能系统全国重点实验室

	Multi-Source Knowledge Reasoning Graph Network for Multi-Modal Commonsense Inference
	Ma, Xuan 1,2,3; Yang, Xiaoshan 1,2,3; Xu, Changsheng 1,2,3
刊名	ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
	2023-07-01
卷号	19 期号:4 页码:17
关键词	Knowledge reasoning multi-modal commonsense inference graph neural network
ISSN号	1551-6857
DOI	10.1145/3573201
通讯作者	Ma, Xuan(maxuan2018@ia.ac.cn)
英文摘要	As a crucial part of natural language processing, event-centered commonsense inference task has attracted increasing attention. With a given observed event, the intention and reaction of the people involved in the event are required to be inferred with artificial intelligent algorithms. To solve this problem, sequence-to-sequence methods are widely studied, where the event is first encoded into a specific representation and then decoded to generate the results. However, all the existing methods learn the event representation only with the textual information, while the visual information is ignored, which is actually helpful for the commonsense reference. In this article, we first define a new task of multi-modal commonsense reference with both textual and visual information. A new event-centered multi-modal dataset is also provided. Then we propose a multi-source knowledge reasoning graph network to solve this task, where three kinds of relational knowledge are considered. Multi-modal correlations are learned to get the event's multi-modal representation from a global perspective. Intra-event object relations are explored to capture the fine-grained event feature with an object graph. Inter-event semantic relations are also explored through the external knowledge to understand the semantic associations among events with an event graph. We conduct extensive experiments on the new dataset, and the results show the effectiveness of our method.
资助项目	National Key Research and Development Program of China[2018AAA0100604] ; National Natural Science Foundation of China[61720106006] ; National Natural Science Foundation of China[62036012] ; National Natural Science Foundation of China[62072455] ; National Natural Science Foundation of China[61721004] ; National Natural Science Foundation of China[U1836220] ; National Natural Science Foundation of China[61872424] ; Beijing Natural Science Foundation[L201001]
WOS研究方向	Computer Science
语种	英语
出版者	ASSOC COMPUTING MACHINERY
WOS记录号	WOS:001011937600003
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/53711]
专题	多模态人工智能系统全国重点实验室
通讯作者	Ma, Xuan
作者单位	1.Univ Chinese Acad Sci, Inst Automat, Chinese Acad Sci, Natl Lab Pattern Recognit, 95 Zhongguancun East Rd, Beijing, Peoples R China 2.Peng Cheng Lab, Shenzhen, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, 95 Zhongguancun East Rd, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Ma, Xuan,Yang, Xiaoshan,Xu, Changsheng. Multi-Source Knowledge Reasoning Graph Network for Multi-Modal Commonsense Inference[J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,2023,19(4):17.
APA	Ma, Xuan,Yang, Xiaoshan,&Xu, Changsheng.(2023).Multi-Source Knowledge Reasoning Graph Network for Multi-Modal Commonsense Inference.ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,19(4),17.
MLA	Ma, Xuan,et al."Multi-Source Knowledge Reasoning Graph Network for Multi-Modal Commonsense Inference".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 19.4(2023):17.