Please wait a minute...
New Technology of Library and Information Service  2007, Vol. 2 Issue (7): 14-17    DOI: 10.11925/infotech.1003-3513.2007.07.04
Current Issue | Archive | Adv Search |
Study on OWL-based Construction Method of Defense Products and Organizations Ontology
Ma Jing1   Xie Juanna1   Hou Junjie2
1(College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)
2(China Aerospace Engineering Consultation Center, Beijing 100037, China)
Download:
Export: BibTeX | EndNote (RIS)      
Abstract  

From the present theory of semantic Web and Ontology, the tools and methods to construct OWL-based Ontology about defense organizations and products are explored in this paper. The Ontology of the world defense industry organizations and products is constructed with Protégé3.2. Finally, the relevant visible figure of this Ontology is presented.

Key wordsSemantic Web      Domain Ontology      OWL      Construction method     
Received: 23 May 2007      Published: 25 July 2007
: 

G350.7 

 
     
  TP391

 
Corresponding Authors: Ma Jing     E-mail: majing5525@126.com
About author:: Ma Jing,Xie Juanna,Hou Junjie

Cite this article:

Ma Jing,Xie Juanna,Hou Junjie. Study on OWL-based Construction Method of Defense Products and Organizations Ontology. New Technology of Library and Information Service, 2007, 2(7): 14-17.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2007.07.04     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2007/V2/I7/14

[1] Ushold M. Knowledge level modeling:concepts and terminology[J]. Knowledge Engineering Review, 1998,13(1):5-29.
[2] 陈刚,陆汝钤,金芝.基于领域知识重用的虚拟领域本体构造[J].软件科学,2003,14(3):10-13.
[3] Perez A G, Benjamins V R. Overview of Knowledge Sharing and Reuse Components: Ontologies and Problem Solving Methods[C]. In:Benjamins V R,Chandrasekaran B, Gomez Perez A, et al.Proceedings of the IJCAI-99 Workshop on Ontologies and Problem-Solving Methods(KRR5). Stockholm:Sweden,1999:1-15.
[4] OWL Web Ontology Language Guide[EB/OL].[2007-05-17]. http://www.w3.org/TR/owl-guide/.
[5] Protégé[EB/OL].[2007-05-17]. http://Protege.stanford.edu.
[6] Transforming the Defense Industrial Base: A Roadmap[EB/OL]. [2007-05-17]. http://www.acq.osd.mil/ip/.
[7] 军工先进制造技术信息网[EB/OL].[2007-05-17]. http://www.diamt.net.cn/.
[8] 国防在线网站[EB/OL].[2007-05-17]. http://www.defenseonline.com.cn/index.htm.
[9] 中国航空信息网[EB/OL].[2007-05-17]. http://www.aeroinfo.com.cn/.
[10] 中国军民两用高技术网[EB/OL].[2007-05-17]. http://www.chinatoptech.com.
[11] 国家航空局网站[EB/OL].[2007-05-17]. http://www.cnsa.gov.cn/n615708/index.
[12] 国防科工委网站[EB/OL].[2007-05-17]. http://www.costind.gov.cn/.
[13] 中国大百科全书智慧藏[EB/OL]. [2007-05-17]. http://wordpedia.pidc.org.tw/.

[1] Shan Xiaohong,Wang Chunwen,Liu Xiaoyan,Han Shengxi,Yang Juan. Identifying Lead Users in Open Innovation Community from Knowledge-based Perspectives[J]. 数据分析与知识发现, 2021, 5(9): 85-96.
[2] Li Wenna,Zhang Zhixiong. Research on Knowledge Base Error Detection Method Based on Confidence Learning[J]. 数据分析与知识发现, 2021, 5(9): 1-9.
[3] Lu Yunmeng,Liu Tiezhong. Diffusion Model for Tacit Knowledge of Scientific Cooperation Network Based on Relevance: Case Study of Major Sci-Tech Projects[J]. 数据分析与知识发现, 2021, 5(9): 10-20.
[4] Zhou Yang,Li Xuejun,Wang Donglei,Chen Fang,Peng Lijuan. Visualizing Knowledge Graph for Explosive Formula Design[J]. 数据分析与知识发现, 2021, 5(9): 42-53.
[5] Chai Qingfeng, Shi Linyan, Mei Shan, Xiong Haitao, He Huixin. Extracting Knowledge Elements of Sci-Tech Literature Based on Artificial and Machine Features[J]. 数据分析与知识发现, 2021, 5(8): 132-144.
[6] Shen Kejie, Huang Huanting, Hua Bolin. Constructing Knowledge Graph with Public Resumes[J]. 数据分析与知识发现, 2021, 5(7): 81-90.
[7] Ruan Xiaoyun,Liao Jianbin,Li Xiang,Yang Yang,Li Daifeng. Interpretable Recommendation of Reinforcement Learning Based on Talent Knowledge Graph Reasoning[J]. 数据分析与知识发现, 2021, 5(6): 36-50.
[8] Lu Linong,Zhu Zhongming,Zhang Wangqiang,Wang Xiaochun. Cross-database Knowledge Integration and Fingerprint of Institutional Repositories with Lingo3G Clustering Algorithm[J]. 数据分析与知识发现, 2021, 5(5): 127-132.
[9] Li He,Liu Jiayu,Li Shiyu,Wu Di,Jin Shuaiqi. Optimizing Automatic Question Answering System Based on Disease Knowledge Graph[J]. 数据分析与知识发现, 2021, 5(5): 115-126.
[10] Dai Bing,Hu Zhengyin. Review of Studies on Literature-Based Discovery[J]. 数据分析与知识发现, 2021, 5(4): 1-12.
[11] Shi Xiang,Liu Ping. Extraction and Representation of Domain Knowledge with Semantic Description Model and Knowledge Elements——Case Study of Information Retrieval[J]. 数据分析与知识发现, 2021, 5(4): 123-133.
[12] Li Ming, Li Ying, Zhou Qing, Wang Jun. Analyzing Knowledge Demand and Supply of Community Question Answering with TF-PIDF[J]. 数据分析与知识发现, 2021, 5(2): 106-115.
[13] Yu Chuanming, Zhang Zhengang, Kong Lingge. Comparing Knowledge Graph Representation Models for Link Prediction[J]. 数据分析与知识发现, 2021, 5(11): 29-44.
[14] Hua Bin, Wu Nuo, He Xin. Integrating Expert Reviews for Government Information Projects with Knowledge Fusion[J]. 数据分析与知识发现, 2021, 5(10): 124-136.
[15] Chen Shiji, Qiu Junping, Yu Bo. Topic Analysis of LIS Big Data Research with Overlay Mapping[J]. 数据分析与知识发现, 2021, 5(10): 51-59.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn