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New Technology of Library and Information Service  2011, Vol. 27 Issue (1): 22-30    DOI: 10.11925/infotech.1003-3513.2011.01.04
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Study on the Mapping Mechanism Between WordNet and SUMO Ontology
Wang Xiaoyue, Hu Zewen, Bai Rujiang
Institute of Scientific & Technical Information, Shandong University of Technology, Zibo 255049, China
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To solve the existing contradiction of generality and speciality between Ontology concepts and natural language words,this paper takes WordNet thesaurus and SUMO Ontology as research objects, makes a simple introduction of them, detailedly analyzes the mapping motivations between them, proposes a mapping model among natural language words, WordNet synsets and SUMO Ontology concepts, and deeply analyzes the mapping instances, the mapping effects and applications between WordNet synsets and SUMO Ontology concepts. The authors hopes to better utilize the mapping relations between WordNet and SUMO to solve the contradiction between Ontology concepts and natural language words, and make Ontology have a more widely application in intelligent retrieval, semantic classification and data mining etc.

Key wordsWordNet      SUMO Ontology      Mapping motivation      Mapping model      Mapping instance      Mapping effect     
Received: 02 November 2010      Published: 12 February 2011

G250 TP391


Cite this article:

Wang Xiaoyue, Hu Zewen, Bai Rujiang. Study on the Mapping Mechanism Between WordNet and SUMO Ontology. New Technology of Library and Information Service, 2011, 27(1): 22-30.

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[1] Ginter F, Pyysalo S, Boberg J, et al. Ontology-based Feature Transformations: A Data-driven Approach. In: Proceedings of the 4th International Conference, EsTAL 2004-Advances in Natural Language Processing. Berlin: Springer, 2004: 279-290.

[2] 李文,陈叶旺,彭鑫,等.一种有效的基于本体的词语-概念映射方法
[J]. 计算机科学 ,2010,37(10):138-142.

[3] Suggested Upper Merged Ontology (SUMO).

[4] Sigma Knowledge Engineering Environment.

[5] DBpedia.

[6] Welcome to Wikipedia. wiki/Main_Page.

[7] The Open Biological and Biomedical Ontologies.

[8] Standard Upper Ontology Knowledge Interchange Format.

[9] Graphviz - Graph Visualization Software.

[10] Translating UNL Expressions to Logical Expressions.

[11] Sevcenko M. Online Presentation of an Upper Ontology. http://www.

[12] Miller G A, Beckwith R, Fellbaum C, et al. Introduction to WordNet: An On-line Lexical Database
[J]. International Journal of Lexicography, 1990, 3 (4): 235-244.

[13] Wnstats - WordNet 3.0 Database Statistics.

[14] Niles I, Pease A. Linking Lexicons and Ontologies: Mapping WordNet to the Suggested Upper Merged Ontology. In: Proceedings of the 2003 International Conference on Information and Knowledge Engineering (IKE 03), Las Vegas.2003: 23-26.

[15] Pease A, Niles I, Li J. The Suggested Upper Merged Ontology: A Large Ontology for the Semantic Web and Its Applications. In: Working Notes of the AAAI-2002 Workshop on Ontologies and the Semantic Web, Edmonton, Canada.2002.

[16] Miller G A. WordNet: A Lexical Database for English
[J]. Communications of the ACM, 1995, 38(11): 39-41.

[17] 詹卫东.WordNet 简介.

[18] Song S X, Zhang J, Li C P. Concept Chain Based Text Clustering. In: Proceedings of 2005 International Conference on Computational Intelligence and Security (CIS 2005).Berlin: Springer-Verlag, 2005:713-720.

[19] 张剑,李春平. 基于WordNet 概念向量空间模型的文本分类
[J]. 计算机工程与应用 ,2006,42(4):174-178.

[20] Lee Y H, Tsao W J, Chu T H. Use of Ontology to Support Concept-based Text Categorization. In: Proceedings of Designing E-Business Systems: Markets, Services, and Networks, the 7th Workshop on E-Business, Web 2008.LNBIP 22. Heidelberg: Springer-Verlag, 2009: 201-213.

[21] Publications.

[22] Ahrens K, Chung S F,Huang C R. From Lexical Semantics to Conceptual Metaphors: Mapping Principle Verification with WordNet and SUMO. In: Proceedings of the 5th Chinese Lexical Semantics Workshop(CLSW-5). Singapore:COLIPS, 2004:99-106.

[23] 时念云, 杨晨. 基于领域本体的语义标注方法研究
[J]. 计算机工程与设计 ,2007,28(24):5985-5987.

[24] Abdelwahab A, Sekiya H, Matsuba I, et al. An Efficient Collaborative Filtering Algorithm Using SVD-free Latent Semantic Indexing and Particle Swarm Optimization. In: Proceedings of 2009 International Conference on Natural Language Processing and Knowledge Engineering, NLP-KE 2009. Piscataway: IEEE Computer Society, 2009:1-4.

[25] 张真.基于语义相似度的中文文本分类系统的研究与实现. 大连: 大连海事大学,2007.

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