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New Technology of Library and Information Service  2016, Vol. 32 Issue (10): 13-24    DOI: 10.11925/infotech.1003-3513.2016.10.02
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Semantic Text Mining Methodologies for Intelligence Analysis
Zhao Dongxiao(),Wang Xiaoyue,Bai Rujiang,Liu Ziqiang
Institute of Scientific & Technical Information, Shandong University of Technology, Zibo 255049, China
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Abstract  

[Objective] This paper reviews the semantic text mining techniques for intelligence analysis. [Coverage] We surveyed the leading semantic text mining research on intelligence analysis from the last ten years and a few earlier studies. [Methods] We first discussed the semantic text mining methodologies and algorithms for words, sentences and paragraphs. Then, we analyzed these techniques from the perspective of topic evolution and applications of mining technologies. [Results] Compared to the traditional intelligence analysis methods, semantic text mining approaches could process unstructured data and deal with multi-layer structured data. [Limitations] Only reviewed the leading studies and their applications in the scientific field. [Conclusions] Semantic text mining improve the performance of traditional intelligence analysis systems and become the future direction of research methodology. More research is needed to enrich the outlier semantic resources.

Key wordsSemantic text mining      Intelligence analysis      Topic evolution      Technology mining     
Received: 06 June 2016      Published: 23 November 2016

Cite this article:

Zhao Dongxiao,Wang Xiaoyue,Bai Rujiang,Liu Ziqiang. Semantic Text Mining Methodologies for Intelligence Analysis. New Technology of Library and Information Service, 2016, 32(10): 13-24.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2016.10.02     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2016/V32/I10/13

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