Increasing Interpretation of Web Topic Detection via Prototype Learning From Sparse Poisson Deconvolution

doi:10.1109/TCYB.2018.2795015

	Increasing Interpretation of Web Topic Detection via Prototype Learning From Sparse Poisson Deconvolution
	Pang, Junbiao 1; Hu, Anjing 1; Huang, Qingming 2,3; Tian, Qi 4; Yin, Baocai 5
	2019-03-01
发表期刊	IEEE TRANSACTIONS ON CYBERNETICS
ISSN	2168-2267
卷号	49 期号:3 页码:1072-1083
摘要	Organizing webpages into interesting topics is one of the key steps to understand the trends from multimodal Web data. The sparse, noisy, and less-constrained user-generated content results in inefficient feature representations. These descriptors unavoidably cause that a detected topic still contains a certain number of the false detected webpages, which further make a topic be less coherent, less interpretable, and less useful. In this paper, we address this problem from a viewpoint interpreting a topic by its prototypes, and present a two-step approach to achieve this goal. Following the detection-by-ranking approach, a sparse Poisson deconvolution is proposed to learn the intratopic similarities between webpages. To find the prototypes, leveraging the intratopic similarities, top-k diverse yet representative prototype webpages are identified from a submodularity function. Experimental results not only show the improved accuracies for the Web topic detection task, but also increase the interpretation of a topic by its prototypes on two public datasets.
关键词	Poisson deconvolution prototype learning (PL) sparsity submodularity topic interpretation Web topic detection
DOI	10.1109/TCYB.2018.2795015
收录类别	SCI
语种	英语
资助项目	Natural Science Foundation of China[61672069] ; Natural Science Foundation of China[61472387] ; Natural Science Foundation of China[61332016] ; Natural Science Foundation of China[U1636214] ; Natural Science Foundation of China[61650202] ; Natural Science Foundation of China[61620106009] ; Natural Science Foundation of China[61429201] ; National Basic Research Program of China (973 Program)[2015CB351800] ; China Post-Doctoral Research Foundation ; Beijing Municipal Commission of Education[KM201610005034] ; Key Research Program of Frontier Sciences, Chinese Academy of Sciences[QYZDJ-SSW-SYS013] ; ARO[W911NF-15-1-0290] ; NEC Laboratory of America ; NEC Laboratoriy of Blippar
WOS研究方向	Automation & Control Systems ; Computer Science
WOS类目	Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号	WOS:000458655900029
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/3415
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Pang, Junbiao; Huang, Qingming
作者单位	1.Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Multimedia & Intelligent Software, Beijing 100124, Peoples R China 2.Univ Chinese Acad Sci, Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 4.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA 5.Dalian Univ Technol, Adv Invocat Ctr Future Internet Technol, Dalian 116024, Peoples R China
推荐引用方式 GB/T 7714	Pang, Junbiao,Hu, Anjing,Huang, Qingming,et al. Increasing Interpretation of Web Topic Detection via Prototype Learning From Sparse Poisson Deconvolution[J]. IEEE TRANSACTIONS ON CYBERNETICS,2019,49(3):1072-1083.
APA	Pang, Junbiao,Hu, Anjing,Huang, Qingming,Tian, Qi,&Yin, Baocai.(2019).Increasing Interpretation of Web Topic Detection via Prototype Learning From Sparse Poisson Deconvolution.IEEE TRANSACTIONS ON CYBERNETICS,49(3),1072-1083.
MLA	Pang, Junbiao,et al."Increasing Interpretation of Web Topic Detection via Prototype Learning From Sparse Poisson Deconvolution".IEEE TRANSACTIONS ON CYBERNETICS 49.3(2019):1072-1083.