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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (4): 84-93    DOI: 10.11925/infotech.2096-3467.2017.04.10
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Building Semantic Enrichment Framework for Scientific Literature Retrieval System
Jing Xie,Jingdong Wang,Zhenxin Wu(),Zhixiong Zhang,Ying Wang,Zhifei Ye
National Science Library, Chinese Academy of Sciences, Beijing 100190, China
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Abstract  

[Objective] This paper aims to improve the scientific literature retrieval system with the help of semantic recognition and knowledge relationship computing. [Methods] First, we identified and extracted semantic objects from the scientific literature. Then, we calculated and established semantic relations among the objects using data-mining tools. Finally, we built semantic multidimensional index for these objects and relations, and then designed a new data organization model. [Results] The new system effectively identified the semantic information and improved the user experience. [Limitations] We need to expand the dataset used in this study and evaluate the new system in other areas. [Conclusions] The proposed system could retrieve more knowledge and indicate some future directions.

Key wordsSemantic Enrichment      Semantic Knowledge Organization      Semantic Relation Presentation      Multidimensional Index     
Received: 03 March 2017      Published: 24 May 2017

Cite this article:

Jing Xie,Jingdong Wang,Zhenxin Wu,Zhixiong Zhang,Ying Wang,Zhifei Ye. Building Semantic Enrichment Framework for Scientific Literature Retrieval System. Data Analysis and Knowledge Discovery, 2017, 1(4): 84-93.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.04.10     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I4/84

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