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New Technology of Library and Information Service  2010, Vol. 26 Issue (2): 1-6    DOI: 10.11925/infotech.1003-3513.2010.02.01
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Description of Ontology Modules Based on Granularity
Guo Wenli  Zhang Xiaolin2
1(Library of Beijing University of Posts and Telecommunications, Beijing 100876, China)
2(National Science Library, Chinese Academy of Sciences, Beijing 100190, China)
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Abstract  

To satisfy the various Ontology demands from different perspectives and hierarchies, this paper proposes a new description of Ontology modules based on granularity theory, by which the users can easily extract the modules from existing large Ontologies. Through combining granular computing and faceted classification, this paper defines the granular properties of the Ontology and gives the definition of Ontology granular partitioning as well as its semantic explanation.

Key wordsOntology      Module      Granularity      Facet      Hierarchy     
Received: 30 January 2010      Published: 25 February 2010
: 

G250.76

 
Corresponding Authors: Guo Wenli     E-mail: guowl@bupt.cn
About author:: Guo Wenli,Zhang Xiaolin

Cite this article:

Guo Wenli,Zhang Xiaolin. Description of Ontology Modules Based on Granularity. New Technology of Library and Information Service, 2010, 26(2): 1-6.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2010.02.01     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2010/V26/I2/1

[1] Bodenreider O. The Unified Medical Language System (UMLS): Integrating Biomedical Terminology [J]. Nucleic Acids Research, 2004, 32(suppl_1): 267-270.
[2] Borgida A, Serafini L. Distributed Description Logics: Directed Domain Correspondences in Federated Information Sources [C]. In: Proceedings of the 10th International Conference on Cooperative Information Systems, University of California, Irvine. 2002: 36–53.
[3] Kutz O, Lutz C, Wolter F, et al. ε-Connections of Abstract Description Systems [J]. Artificial Intelligence, 2004, 156(1): 1–73.
[4] Kutz O. ε-Connections and Logics of Distance [D]. Liverpool: University of Liverpool, 2004.
[5] Bao J. Representing and Reasoning with Modular Ontologies [D]. Ames: Iowa State University, 2007.
[6] Bao J, Caragea D, Honavar V. A Distributed Tableau Algorithm for Package-based Description Logics [C/OL]. In: Proceedings of the 2nd International Workshop on Context Representation and Reasoning, Co-located with ECAI 2006.[2010-01-12]. http://www.cs.iastate.edu/~honavar/Papers/bao-crr2006.pdf.
[7] 郭文丽, 张晓林. 本体模块化: 特征、描述与方法 [J]. 图书馆杂志, 2008,27(9): 50-55.
[8] Yao J T, Yao Y Y. A Granular Computing Approach to Machine Learning [C]. In: Proceedings of the 1st International Conference on Fuzzy Systems and Knowledge Discovery,Singapore.2002: 732-736.
[9] 刘炜, 李大玲, 夏翠娟. 元数据与知识本体[J]. 图书馆杂志, 2004,23(6): 50-54.
[10] 董慧, 姜赢, 高巾,等. 基于数字图书馆的本体演化和知识管理研究(I)——本体分子理论 [J]. 情报学报, 2009,28(3): 323-330.
[11] Yao Y Y. A Partition Model of Granular Computing[J]. LNCS Transactions on Rough Sets, 2004 (1): 232-253.
[12] Dorn C, Schall D, Dustdar S. Granular Context in Collaborative Mobile Environments [C]. In:  Proceedings of International Workshop on Context-Aware Mobile Systems CAMS’06, Montpellier, France.2006: 1904-1913.
[13] Kumar A, Smith B. Ontology for Task-based Clinical Guidelines and the Theory of Granular Partitions [C]. In: Proceedings of the 9th Conference on Artificial Intelligence in Medicine in Europe, Protaras, Cyprus.2003: 71-75.
[14] Vider K, Orav H. WordNet: An On-line Lexical Database [EB/OL]. [2010-01-22]. http://www.cl.ut.ee/yllitised/viderorav.html.
[15] Wine本体[EB/OL]. [2010-01-22].http://www.w3.org/TR/2004/REC-owl-guide-20040210/wine.
[16] William S, Austin T. Ontologies [J]. IEEE Intelligent Systems, 1999,14(1-2): 18-19.
[17] 郭世星. 分面元数据系统实例分析与评价 [D]. 南京: 南京农业大学,2007.
[18] Marti H. Clustering Versus Faceted Categories for Information Exploration [J]. Communications of the ACM, 2006,49(4): 59-61.
[19] William D. How to Make a Faceted Classification and Put It on the Web [EB/OL].  (2009-03-28). [2010-01-22]. http://www.miskatonic.org/library/facet-web-howto.html.
[20] Harter S P. Online Information Retrieval: Concepts, Principles and Techniques [M]. Orlando, FL, USA:Academic Press Inc., 1986: 244-245.
[21] Ranganathan S R. Classification and Communication[M]. Delhi, India:University of Delhi,  1951: 215-287.

 

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