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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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[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.

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[1] U.S.National Library of Medicine. Semantic Knowledge Representation [EB/OL].[2016-01-13].
[2] Wikipedia. Knowledge Graph [EB/OL].[2016-02-10].
[3] Google Inside Search [EB/OL]. [2016-02-10].
[4] Wolframalpha. Computational Knowledge Engine [EB/OL].[2015-03-10].
[5] Kngine. The Most Intelligent Engine [EB/OL]. [2015-03-10].
[6] SindiceTech. Enterprise Knowledge Graphs [EB/OL]. [2015- 03-10].
[7] W3C Semantic Web. RDF [EB/OL].[2015-06-05].
[8] SindiceTech. FreeBase Distribution [EB/OL]. [2015-03-10].
[9] Apache Solr [EB/OL]. [2015-06-05].
[10] PubMed [EB/OL]. [2015-10-11].
[11] U.S.National Library of Medicine. SemRep [EB/OL].[2015-10-22].
[12] Del Corro L, Gemulla R.ClausIE: Clause-Open Information Extraction[C]//Proceedings of the the 22nd International Conference on World Wide Web. 2013:355-366.
[13] Merrill M D.Knowledge Objects[R]. USA: CBT Solutions, 1998: 1-11.
[14] U.S.National Library of Medicine. Unified Medical Language System (UMLS) [EB/OL].[2016-01-13]. .
[15] 王颖, 张智雄, 李传席, 等. 科技知识组织体系开放引擎系统的设计与实现[J]. 现代图书情报技术,2015 (10): 95-101.
[15] (Wang Ying, Zhang Zhixiong, Li Chuanxi, et al.The Design and Implementation of Open Engine System for Scientific & Technological Knowledge Organization Systems[J]. New Technology of Library and Information Service, 2015 (10): 95-101.)
[16] UMLS. Semantic Relationships [EB/OL].[2015-10-17].
[17] Chakraborty A, Munshi S, Mukhopadhyay D.Searching and Establishment of S-P-O Relationships for Linked RDF Graphs: An Adaptive Approach[C]//Proceedings of International Conference on Cloud & Ubiquitous Computing & Emerging Technologies (CUBE). 2013.
[18] Matthews P H.Syntactic Relations:A Critical Survey[M]. University of CambridgePress, 2007: 3-10.
[19] U.S.National Library of Medicine. Medical Subject Headings (MeSH) [EB/OL].[2015-06-05].
[20] U.S.National Library of Medicine. MeSH Category Tree View [EB/OL].[2015-06-05].
[21] MetaMap - A Tool For Recognizing UMLS Concepts in Text [EB/OL]. [2015-06-20].
[22] The Stanford Natural Language Processing Group. Stanford Part of Speech Tagger [EB/OL].[2015-08-24].
[23] SPECIALIST dTagger [EB/OL]. [2015-06-20].
[24] 孙坦, 刘峥. 面向外文科技文献信息的知识组织体系建设思路[J]. 图书与情报, 2013 (1): 2-7.
[24] (Sun Tan, Liu Zheng.Methodology Framework of Knowledge Organization System for Scientific & Technological Literature[J]. Library & Information, 2013(1): 2-7.)
[25] Rindflesch T C, Fiszman M.The Interaction of Domain Knowledge and Linguistic Structure in Natural Language Pprocessing: Interpreting Hypernymic Propositions in Biomedical Text[J]. Journal of Biomedical Informatics, 2003, 36(6): 462-477.
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