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Text mining based theme logic structure identification: application in library journals
Zhu, Qing1; Wu, Yiqiong1; Li, Yuze2; Han, Jing1; Zhou, Xiaoyang1,3
2018
Source PublicationLIBRARY HI TECH
ISSN0737-8831
Volume36Issue:3Pages:411-425
AbstractPurpose Library intelligence institutions, which are a kind of traditional knowledge management organization, are at the frontline of the big data revolution, in which the use of unstructured data has become a modern knowledge management resource. The paper aims to discuss this issue. Design/methodology/approach This research combined theme logic structure (TLS), artificial neural network (ANN), and ensemble empirical mode decomposition (EEMD) to transform unstructured data into a signal-wave to examine the research characteristics. Findings Research characteristics have a vital effect on knowledge management activities and management behavior through concentration and relaxation, and ultimately form a quasi-periodic evolution. Knowledge management should actively control the evolution of the research characteristics because the natural development of six to nine years was found to be difficult to plot. Originality/value Periodic evaluation using TLS-ANN-EEMD gives insights into journal evolution and allows journal managers and contributors to follow the intrinsic mode functions and predict the journal research characteristics tendencies.
KeywordBig data Knowledge management Machine learning Text mining ANN EEMD
DOI10.1108/LHT-10-2017-0211
Language英语
Funding ProjectNational Natural Science Foundation of China[71401093] ; National Natural Science Foundation of China[71350007] ; National Natural Science Foundation of China[91646113]
WOS Research AreaInformation Science & Library Science
WOS SubjectInformation Science & Library Science
WOS IDWOS:000434253200004
PublisherEMERALD GROUP PUBLISHING LTD
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/30365
Collection中国科学院数学与系统科学研究院
Affiliation1.Shaanxi Normal Univ, Inst Cross Proc Percept & Control, Xian, Shaanxi, Peoples R China
2.Univ Toronto, Dept Mech & Ind Engn, Toronto, ON, Canada
3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Zhu, Qing,Wu, Yiqiong,Li, Yuze,et al. Text mining based theme logic structure identification: application in library journals[J]. LIBRARY HI TECH,2018,36(3):411-425.
APA Zhu, Qing,Wu, Yiqiong,Li, Yuze,Han, Jing,&Zhou, Xiaoyang.(2018).Text mining based theme logic structure identification: application in library journals.LIBRARY HI TECH,36(3),411-425.
MLA Zhu, Qing,et al."Text mining based theme logic structure identification: application in library journals".LIBRARY HI TECH 36.3(2018):411-425.
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