Please wait a minute...
New Technology of Library and Information Service  2009, Vol. 25 Issue (11): 23-28    DOI: 10.11925/infotech.1003-3513.2009.11.05
article Current Issue | Archive | Adv Search |
Research on Knowledge Integration Model Based on Ontology
Wang Xin1,2   Xu Baoxiang1
1(School of Management,Jilin University,Changchun 130022,China)
2(Qiqihar Medical College Library,Qiqihar 161006,China)
Download: PDF (525 KB)  
Export: BibTeX | EndNote (RIS)      
Abstract  

 Firstly,this paper adopts the methods of classification and description on Ontology, and researches the process of knowledge integration modeling by Ontology mapping and multi-Ontology management technique.Secondly,it introduces the structure model of knowledge integration and gives the example to test the process of knowledge integration model.Thirdly,the conclusion shows that introducing Ontology in the process of knowledge integration modeling can reduce defects of unclear meaning and guarantee the consistence among concept classes.

Key wordsOntology      Example      Knowledge integration      Model     
Received: 09 October 2009      Published: 25 November 2009
ZTFLH: 

G35

 
Corresponding Authors: Wang Xin     E-mail: wanghongwei419@163.com
About author:: Wang Xin,Xu Baoxiang

Cite this article:

Wang Xin,Xu Baoxiang. Research on Knowledge Integration Model Based on Ontology. New Technology of Library and Information Service, 2009, 25(11): 23-28.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2009.11.05     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2009/V25/I11/23

[1] 黄智生.语义支撑的知识技术[EB/OL]. [2009-03-09]. http://bbs.xml.org.cn/temp/sekt040727.rar.
[2] Devedzic V.A Survey of Modern Knowledge Modeling Techniques [J]. Expert Systems with Application,1999,17(4):275-294.
[3]  顾芳,曹存根.知识工程中的本体研究现状与存在问题[J].计算机科学,2004,27(10):25-29.
[4]  Wache H, Vgele T, Visser V,et al. Ontology-based Integration of Information-A Survey of Existing Approaches [C].In:Proceedings of the IJCAI-01 Workshop: Ontology and Information Sharing,USA. 2008:3-6.
[5]  Robert M, Colomb J. Formal Versus Material Ontology for Information Systems Interoperation in the Semantic Web[J].The Computer Journal London,2006,49(1):4-15.
[6]  张磊,王金栋,谢强,等.基于Ontology的企业知识集成研究[J].武汉大学学报:工学版,2005,38(4):84-87.
[7]  Natalya F, Michel K. Ontology Evolution: Not the Same as Schema Evolution[J]. Knowledge and Information Systems, 2004, 16(6):428-440.
[8]  Chang E, Wouters C, Dillon T S, et al. Ontologies on the MOVE[C].Database Systems for Advanced Application [C]. In:Proceedings of the 9th International Conference of Databases Systems for Advanced Application, Jeju Island,Korea. 2003.
[9] Omelayenko B, Fense D. Mapping Technology for Enterprise Integration [EB/OL]. [2009-03-17].http://www.cs.vu.nc/borys/papers/FLATRS02.pdf.
[10]  Helena S, Joao P. Ontology: How can They be Built? [J].Knowledge and Information Systems, 2004,16(4): 430-441.
[11]  Farrugia J. Model-Theoretic Semantic for the Web[C]. In:Proceedings of the 12th International Conference on World Wide Web(WWW2003).Budapest Hungary: ACM Press,2008:29-38.
[12]  Uschold M. Where are the Semantics in the Semantic Web [J].AI Magazine, 2003, 24(3):25-36.
[13]  Jimmy C,Newell S. Knowledge Integration Processes and Dynamics Within the Context of Cross-functional Projects[J]. International Journal of Project Management, 2008, 21(3):167-176.
[14]   Choi B,Henson K, Raghu T S, et al. Knowledge Sharing Ontology to Facilitate Adopting [J]. Communications of the ACM, 2004, 47(11):85-90.
[15]  刘柏嵩.基于知识的语义网:概念、技术及挑战[J].中国图书馆学报,2003(2):18-19.

[1] Zhao Yang, Zhang Zhixiong, Liu Huan, Ding Liangping. Classification of Chinese Medical Literature with BERT Model[J]. 数据分析与知识发现, 2020, 4(8): 41-49.
[2] Xu Chenfei, Ye Haiying, Bao Ping. Automatic Recognition of Produce Entities from Local Chronicles with Deep Learning[J]. 数据分析与知识发现, 2020, 4(8): 86-97.
[3] Wei Wu, Xie Xingzheng. The Determinants of Continuance Intention to Pay: Empirical Research from Online Knowledge Payment Users[J]. 数据分析与知识发现, 2020, 4(8): 119-129.
[4] Shen Zhihong,Zhao Zihao,Wang Haibo. Big Data Technology Stack Shifting: From SQL Centric to Graph Centric[J]. 数据分析与知识发现, 2020, 4(7): 50-65.
[5] Wang Xinyun,Wang Hao,Deng Sanhong,Zhang Baolong. Classification of Academic Papers for Periodical Selection[J]. 数据分析与知识发现, 2020, 4(7): 96-109.
[6] Yue Lixin,Liu Ziqiang,Hu Zhengyin. Evolution Analysis of Hot Topics with Trend-Prediction[J]. 数据分析与知识发现, 2020, 4(6): 22-34.
[7] Cai Yongming,Liu Lu,Wang Kewei. Identifying Key Users and Topics from Online Learning Community[J]. 数据分析与知识发现, 2020, 4(6): 69-79.
[8] Su Qing,Chen Sizhao,Wu Weimin,Li Xiaomei,Huang Tiankuan. Personalized Recommendation Model Based on Collaborative Filtering Algorithm of Learning Situation[J]. 数据分析与知识发现, 2020, 4(5): 105-117.
[9] Deng Siyi,Le Xiaoqiu. Coreference Resolution Based on Dynamic Semantic Attention[J]. 数据分析与知识发现, 2020, 4(5): 46-53.
[10] Wei Guohui,Zhang Fengcong,Fu Xianjun,Wang Zhenguo. Similarity Measurement of Traditional Chinese Medicine Components for Cold-hot Nature Discrimination[J]. 数据分析与知识发现, 2020, 4(5): 75-83.
[11] Yu Chuanming,Yuan Sai,Zhu Xingyu,Lin Hongjun,Zhang Puliang,An Lu. Research on Deep Learning Based Topic Representation of Hot Events[J]. 数据分析与知识发现, 2020, 4(4): 1-14.
[12] Zhang Dongyu,Cui Zijuan,Li Yingxia,Zhang Wei,Lin Hongfei. Identifying Noun Metaphors with Transformer and BERT[J]. 数据分析与知识发现, 2020, 4(4): 100-108.
[13] Yang Xu,Qian Xiaodong. Synchronous Clustering Algorithm for Social Networks Based on Improved Vicsek Model[J]. 数据分析与知识发现, 2020, 4(4): 119-128.
[14] Pan Youneng,Ni Xiuli. Recommending Online Medical Experts with Labeled-LDA Model[J]. 数据分析与知识发现, 2020, 4(4): 34-43.
[15] Shen Zhuo,Li Yan. Mining User Reviews with PreLM-FT Fine-Grain Sentiment Analysis[J]. 数据分析与知识发现, 2020, 4(4): 63-71.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn