期刊文献+

基于领域本体模型的概念语义相似度计算研究 被引量:16

Research on Concept Semantic Similarity Computation Based on Domain Ontology Model
下载PDF
导出
摘要 随着本体在信息检索、人工智能等领域的广泛应用,面向本体的概念相似度计算成为本体研究的一大热点。目前领域本体中概念相似度的研究主要是利用概念的上下位关系进行计算,但这并没有完整反映出概念的语义信息。本文首先在本体模型的基础上提出领域本体模型的八元组表示方法和领域本体概念的九元组表示方法,给出领域本体模型的DCG图。然后以提出领域本体模型为基础构建概念语义相似度计算的MD4模型,该模型全面考虑概念的属性、上下位语义结构关系、自定义语义关系和实例特征对相似度的影响,通过综合计算,得到领域本体中概念的实际相似度。本文最后以动车组专业本体作为实验对象,对MD4模型进行验证。实验结果表明,该计算模型充分利用概念的语义信息,得到的结果也比较合理。 Along with the widespread application of ontology in the fields of information retrieval and artificial intelligence etc,the concept similarity computation of domain ontology has become the focus research field.Currently,most research on concept similarity computation is based on "is a" relation between concepts,however,it does not utilize the concept semantic information completely.Firstly,on the basis of ontology model,this paper proposes an Eight-tuples model for domain ontology and a Nine-tuples model for its concept.We can use the Directed Cyclic Graph(DCG) to formalize the domain ontology.Then this paper builds the fourfold Matching-Distance Model(MD4) to compute concept semantic similarity based the on domain ontology model.This MD4 model has comprehensive consideration about the property,"is-a" relation,"user-defined" relation and instance of concept.And through integration computation,we can get the true concept similarity.Finally,this paper makes an experiment on the EMU ontology that was built in the high-speed railway domain.The experiment shows that the method utilizes the concept semantic information fully and the computation result is reasonable.
作者 刘紫玉 黄磊
出处 《铁道学报》 EI CAS CSCD 北大核心 2011年第1期52-57,共6页 Journal of the China Railway Society
基金 铁道部科技研究开发计划(Z2006-94) 教育部科技基础资源数据平台(507002) 河北省高等学校科学研究计划(Z2010257)
关键词 本体 领域本体 语义相似度 MD4计算模型 ontology domain ontology semantic similarity fourfold matching-distance model(MD4 model)
  • 相关文献

参考文献12

  • 1KLEIN M, BERNSTEIN A. Searching for Services on the Semantic: Web Using Process Ontologies[C]// Proceedings of the International Semantic Web Working Symposium(SWWS). Amsterdam: IOSPress, 2001:159- 172.
  • 2金芝.知识工程中的本体论研究[C].陆汝钤.世纪之交的知识工程与知识科学.北京:清华大学出版社,2001,9:447—468.
  • 3张德.万维网信息聚类研究[D].南京:东南大学计算机系,2002.
  • 4LEACOCK C, CHODOROW M. Combining Local Context and WordNet Similarity for Word Sense Identification [C]//FELBAUM C. WordNet: An Electronic Lexical Database. Cambridge:MIT Press, 1998: 265-283.
  • 5LIND. An Information-Theoretic Definition of Similarity [C]//Proeeedings of the Fifteenth International Conference on Machine Learning. San Francisco, 1998,296- 304.
  • 6RESNIK O. Semantic Similarity in a Taxonomy: An Information-Based Measure and Its Application to Problems of Ambiguity and Natural Language[J]. Journal of Artificial Intelligence Research, 1999, 11: 95-130.
  • 7TERVSKY A. Features of Similarity[J]. Psychological Review, 1977, 84(2): 327-352.
  • 8Jerome David and Jerome Euzenat. Comparison between Ontology Distances (Preliminary Results) [C]//Proceedings of the 7th Conference on International Semantic Web Conference. Karlsruhe,2008 : 245-260.
  • 9黄果,周竹荣.基于领域本体的概念语义相似度计算研究[J].计算机工程与设计,2007,28(10):2460-2463. 被引量:67
  • 10STUDER R, et al. Knowledge Engineering: Principles and Methods [J]. Data and Knowledge Engineering, 1998, 25(1-2): 161-197.

二级参考文献17

  • 1朱礼军,陶兰,刘慧.领域本体中的概念相似度计算[J].华南理工大学学报(自然科学版),2004,32(z1):147-150. 被引量:48
  • 2张小峰,唐新亭,赵永升,李明.基于本体技术的Internet智能搜索研究[J].计算机工程与设计,2006,27(7):1194-1197. 被引量:6
  • 3董振东 董强.知网简介[EB/OL].http://www.keenage.com/.,1999.
  • 4KLEIN M,BERNSTEIN A.Searching services on the semantic:Web using process ontologies[C]//Proceedings of the International Semantic Web Working Symposium (SWWS).Amster2,dam:IOS Press,2001:159-172.
  • 5RESNIK P.Using information content to evaluate semantic similarity[C]//Proceedings of the 14th International Joint Conference on Artificial Intelligence.Montereal,1995:448-453.
  • 6JIANG J,CONRATH D.Semantic similarity based on corpus statistics and lexical taxonomy[C]//Proceeding of International Conference on Research on Computational Linguistics,Taiwan,1997.
  • 7LEACOCK C,CHODOROW M.Combining local context and WordNet similarity for word sense identification[M]//FELLBAUM C.WordNet:An electronic lexical database.[S.l.]:MIT Press,1998:265-283.
  • 8DAGAN I,LEE L,PEREIRA F.Similarity-based models of word cooccurrence probabilities[J].Machine Learning,1999,34 (1):43-69.
  • 9GURBER T.A translation approach to portable ontology specifications[J].Knowledge Acquisition,1993,5 (2):199-220.
  • 10刘群 李素建.基于《知网》的词汇语义相似度计算.中文计算语言学,2002,7(2):59-76.

共引文献98

同被引文献126

引证文献16

二级引证文献60

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部