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New Technology of Library and Information Service  2016, Vol. 32 Issue (4): 8-19    DOI: 10.11925/infotech.1003-3513.2016.04.02
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Analyzing Knowledge Structure Research with LDA Model
Wang Yuefen(),Fu Zhu,Chen Bikun
School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
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Abstract  

[Objective] This paper aims to comprehensively explore the knowledge structure and hotspot distribution of different disciplines, with the help of topic extraction and distribution analysis using LDA (Latent Dirichlet Allocation) model from the perspective of subject classification. [Methods] We collected data from the domestic knowledge flow (KF) field and KF related literature from CNKI and Wangfang database, then grouped these data into 11 categories by Chinese Library Classification. Finally, we extracted 20 hot subjects from documents in 11 disciplines with the help of the LDA topic model. [Results] The content and knowledge points in 11 disciplines were obtained from the analysis of 20 extracted hot topics. [Limitations] We did not compare the proposed method with topic mining research in other fields. The domestic KF hotspots found by our study were not compared to the previous findings. [Conclusions] The proposed method can help us explore the knowledge structure and research trends more comprehensively.

Key wordsKnowledge flow      LDA      Topic extraction      Discipline classification      Structure map      Research focus     
Received: 16 November 2015      Published: 13 May 2016

Cite this article:

Wang Yuefen,Fu Zhu,Chen Bikun. Analyzing Knowledge Structure Research with LDA Model. New Technology of Library and Information Service, 2016, 32(4): 8-19.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2016.04.02     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2016/V32/I4/8

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