CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
Multimedia News Summarization in Search
Li, Zechao1; Tang, Jinhui1; Wang, Xueming1; Liu, Jing2; Lu, Hanqing2
AbstractIt 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.
KeywordDesign Algorithms Performance Human Factors News Summarization Topic Structure Multimodal Hierarchical Latent Dirichlet Allocation Maximum Spanning Tree
WOS HeadingsScience & Technology ; Technology
Indexed BySCI ; SSCI
Funding Organization973 Program(2014CB347600) ; National Natural Science Foundation of China(61522203 ; 61402228)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems
WOS IDWOS:000373911200008
Citation statistics
Cited Times:8[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.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
Recommended Citation
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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