Multimedia News Summarization in Search

doi:10.1145/2822907

	Multimedia News Summarization in Search
	Li, Zechao 1; Tang, Jinhui 1; Wang, Xueming 1; Liu, Jing2 ; Lu, Hanqing2
发表期刊	ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY
	2016-04-01
卷号	7 期号:3
文章类型	Article
摘要	It is a necessary but challenging task to relieve users from the proliferative news information and allow them to quickly and comprehensively master the information of the whats and hows that are happening in the world every day. In this article, we develop a novel approach of multimedia news summarization for searching results on the Internet, which uncovers the underlying topics among query-related news information and threads the news events within each topic to generate a query-related brief overview. First, the hierarchical latent Dirichlet allocation (hLDA) model is introduced to discover the hierarchical topic structure from query-related news documents, and a new approach based on the weighted aggregation and max pooling is proposed to identify one representative news article for each topic. One representative image is also selected to visualize each topic as a complement to the text information. Given the representative documents selected for each topic, a time-bias maximum spanning tree (MST) algorithm is proposed to thread them into a coherent and compact summary of their parent topic. Finally, we design a friendly interface to present users with the hierarchical summarization of their required news information. Extensive experiments conducted on a large-scale news dataset collected from multiple news Web sites demonstrate the encouraging performance of the proposed solution for news summarization in news retrieval.
关键词	Design Algorithms Performance Human Factors News Summarization Topic Structure Multimodal Hierarchical Latent Dirichlet Allocation Maximum Spanning Tree
WOS标题词	Science & Technology ; Technology
DOI	10.1145/2822907
关键词[WOS]	ENTROPY
收录类别	SCI ; SSCI
语种	英语
项目资助者	973 Program(2014CB347600) ; National Natural Science Foundation of China(61522203 ; 61402228)
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Information Systems
WOS记录号	WOS:000373911200008
引用统计	被引频次：24[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/12202
专题	紫东太初大模型研究中心_图像与视频分析
作者单位	1.Nanjing Univ Sci & Technol, Sch Comp Sci & Engn, Nanjing 210094, Jiangsu, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Li, Zechao,Tang, Jinhui,Wang, Xueming,et al. Multimedia News Summarization in Search[J]. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,2016,7(3).
APA	Li, Zechao,Tang, Jinhui,Wang, Xueming,Liu, Jing,&Lu, Hanqing.(2016).Multimedia News Summarization in Search.ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,7(3).
MLA	Li, Zechao,et al."Multimedia News Summarization in Search".ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 7.3(2016).

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