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Deep-MATEM: TEM query image based cross-modal retrieval for material science literature
Li, Hailiang1,2; Guan, Qingxiao2,3; Wang, Haidong1; Dong, Jing2,4
发表期刊MULTIMEDIA TOOLS AND APPLICATIONS
ISSN1380-7501
2018-12-01
卷号77期号:23页码:30269-30290
通讯作者Guan, Qingxiao(258817567@qq.com)
摘要With the rapid increasing of published material science literatures, an effective literature retrieving system is important for researchers to obtain relevant information. In this paper we propose a cross-modal material science literatures retrieval method using transmission electron microscopy(TEM) image as query information, which provide a access of using material experiment generated TEM image data to retrieve literatures. In this method, terminologies are extracted and topic distribution are inferred from text part of literatures by using LDA, and we design a multi-task Convolutional Neuron Network(CNN) mapping query TEM image to the relevant terminologies and topic distribution predictions. The ranking score is calculated from output for query image and text data. Experimental results shows our method achieves better performance than multi-label CCA, Deep Semantic Matching(Deep SM) and Modality-Specific Deep Structure(MSDS).
关键词Cross-Modal Document retrieval Convolutional network Material science
DOI10.1007/s11042-018-6043-0
关键词[WOS]SCALE ; CLASSIFICATION ; FEATURES
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China[U1536105] ; National Natural Science Foundation of China[51474237] ; National Natural Science Foundation of China[U1536120] ; National Natural Science Foundation of China[U1636201] ; National Key Research and Development Program of China[2016YFB1001003]
项目资助者National Natural Science Foundation of China ; National Key Research and Development Program of China
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号WOS:000448401600006
出版者SPRINGER
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/22828
专题智能感知与计算研究中心
通讯作者Guan, Qingxiao
作者单位1.Cent S Univ, Sch Minerals Proc & Bioengn, Changsha 410083, Hunan, Peoples R China
2.Chinese Acad Sci, Inst Informat Engn, State Key Lab Informat Secur, Beijing 100093, Peoples R China
3.Univ Chinese Acad Sci, Sch Cyber Secur, Beijing 100093, Peoples R China
4.Chinese Acad Sci, Inst Automat, Ctr Res Intelligent Percept & Comp, Beijing 100190, Peoples R China
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GB/T 7714
Li, Hailiang,Guan, Qingxiao,Wang, Haidong,et al. Deep-MATEM: TEM query image based cross-modal retrieval for material science literature[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2018,77(23):30269-30290.
APA Li, Hailiang,Guan, Qingxiao,Wang, Haidong,&Dong, Jing.(2018).Deep-MATEM: TEM query image based cross-modal retrieval for material science literature.MULTIMEDIA TOOLS AND APPLICATIONS,77(23),30269-30290.
MLA Li, Hailiang,et al."Deep-MATEM: TEM query image based cross-modal retrieval for material science literature".MULTIMEDIA TOOLS AND APPLICATIONS 77.23(2018):30269-30290.
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