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Graph-based Multimodal Ranking Models for Multimodal Summarization

文献类型：期刊论文

作者Zhu, Junnan3,4; Xiang, Lu3,4; Zhou, Yu2,4; Zhang, Jiajun1,4; Zong, Chengqing3,4
刊名ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING
出版日期2021-07-01
卷号20期号:4页码:21
关键词Multimodal summarization single-modal multimodal ranking unsupervised
ISSN号2375-4699
DOI10.1145/3445794
通讯作者Zhu, Junnan(junnan.zhu@nlpr.ia.ac.cn)
英文摘要Multimodal summarization aims to extract the most important information from the multimedia input. It is becoming increasingly popular due to the rapid growth of multimedia data in recent years. There are various researches focusing on different multimodal summarization tasks. However, the existing methods can only generate single-modal output or multimodal output. In addition, most of them need a lot of annotated samples for training, which makes it difficult to be generalized to other tasks or domains. Motivated by this, we propose a unified framework for multimodal summarization that can cover both single-modal output summarization and multimodal output summarization. In our framework, we consider three different scenarios and propose the respective unsupervised graph-based multimodal summarization models without the requirement of any manually annotated document-summary pairs for training: (1) generic multimodal ranking, (2) modal-dominated multimodal ranking, and (3) non-redundant text-image multimodal ranking. Furthermore, an image-text similarity estimation model is introduced to measure the semantic similarity between image and text. Experiments show that our proposed models outperform the single-modal summarization methods on both automatic and human evaluation metrics. Besides, our models can also improve the single-modal summarization with the guidance of the multimedia information. This study can be applied as the benchmark for further study on multimodal summarization task.
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000721582900007
出版者ASSOC COMPUTING MACHINERY
源URL[http://ir.ia.ac.cn/handle/173211/46440]  
专题模式识别国家重点实验室_自然语言处理
通讯作者Zhu, Junnan
作者单位1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Inst Automat, Natl Lab Pattern Recognit,CAS,Beijing Acad Artifi, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Inst Automat, Natl Lab Pattern Recognit,CAS,Beijing Fanyu Techn, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Inst Automat, Natl Lab Pattern Recognit,CAS, Beijing, Peoples R China
4.Intelligence Bldg,95,Zhongguancun East Rd, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Zhu, Junnan,Xiang, Lu,Zhou, Yu,et al. Graph-based Multimodal Ranking Models for Multimodal Summarization[J]. ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING,2021,20(4):21.
APA Zhu, Junnan,Xiang, Lu,Zhou, Yu,Zhang, Jiajun,&Zong, Chengqing.(2021).Graph-based Multimodal Ranking Models for Multimodal Summarization.ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING,20(4),21.
MLA Zhu, Junnan,et al."Graph-based Multimodal Ranking Models for Multimodal Summarization".ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING 20.4(2021):21.

入库方式： OAI收割

来源：自动化研究所

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