计算机工程

• 人工智能及识别技术 • 上一篇    下一篇

基于最大公共子图的本体映射方法研究

郭竹为 a,刘胜全 a,b,刘艳 a,赵美玲 a,符贤哲 c   

  1. (新疆大学 a.信息科学与工程学院; b.网络信息技术中心; c.软件学院,乌鲁木齐 830046)
  • 收稿日期:2016-05-05 出版日期:2017-05-15 发布日期:2017-05-15
  • 作者简介:郭竹为(1987—),女,硕士研究生,主研方向为语义Web技术;刘胜全,教授;刘艳,副教授、硕士;赵美玲、符贤哲,硕士研究生。
  • 基金项目:
    新疆维吾尔自治区科学基金(2014211A016)。

Research on Ontology Mapping Method Based on Maximum Common Sub-graph

GUO Zhuwei  a,LIU Shengquan  a,b,LIU Yan  a,ZHAO Meiling  a,FU Xianzhe  c   

  1. (a.School of Information Science and Engineering; b.Network Information Technology Center; c.School of Software,Xinjiang University,Urumqi 830046,China)
  • Received:2016-05-05 Online:2017-05-15 Published:2017-05-15

摘要: 本体映射是对两个本体中的各元素建立语义关系,而影响本体映射的关键是相似度的计算方法。针对相似度计算方法中仍存在语义关系不精准的问题,提出一种本体映射方法,把本体映射问题转化为求解最大公共子图的问题。以图结构表示的本体可更好地体现本体结构之间潜在的语义关系,应用最大公共子图提取本体中的公共部分,并用最大公共子图的性质计算2个本体中元素之间的相似度,进而得到2个本体之间的映射关系。实验结果表明,与CtxMatch,COMA相比,该方法在召回率和准确率方面都有一定提高。

关键词: 语义关系, 相似度, 最大公共子图, 本体映射, 图结构

Abstract: Ontology mapping is aimed to establish the semantic relationship of the elements between the two ontologies, and the key to affect the ontology mapping is the method of calculating the similarity. In order to solve the imprecise semantic relation problem of the similarity calculation method, this paper proposes an ontology mapping method, which transforms the ontology mapping problem into the problem of solving the maximum common sub-graph. Ontology with graph structure can better reflect the latent semantic relations between the structure of the body and the maximum common sub-graph is introduced to extract the common parts of the ontology. The properties of the maximum common sub-graph are used to measure the similarity between two ontology elements.Then the mapping relationship between the two ontologies is obtained. Compared with CtxMatch and COMA,the proposed method is proved to have a certain improvement in the recall rate and the precision.

Key words: semantic relationship, similarity, maximum common sub-graph, ontology mapping, graph structure

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