ABox推理计算实体相似度

薛咏 1; 2; 冯博琴 1; 武艳芳 2

doi:10.7652/xjtuxb201509013

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ABox推理计算实体相似度

更新时间：2025-07-09

- ABox推理计算实体相似度
- Measuring Similarity of Entities Based on ABox Reasoning
- 西安交通大学学报 2015年49卷第9期页码：70-76
- 作者机构：
  
  1. 西安交通大学电子与信息工程学院,西安,710049
  2. 西南科技大学信息工程学院,四川,绵阳,621010
- 作者简介：
- 基金信息：
  
  : 2015-01-13。作者简介: 薛咏(1978—),男,博士生;冯博琴(通信作者),男,教授,博士生导师。基金项目: 国家自然科学基金资助项目(61202181);教育部博士学科点专项科研基金资助项目(20130201130002)
- DOI：10.7652/xjtuxb201509013
  中图分类号： TP391
- 网络首发：2015-09-10，
  
  纸质出版：2015
- 稿件说明：
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薛咏 1, 2, 冯博琴 1, 等. ABox推理计算实体相似度[J]. 西安交通大学学报, 2015,49(9):70-76.

Measuring Similarity of Entities Based on ABox Reasoning[J]. 2015, 49(9): 70-76.
薛咏 1, 2, 冯博琴 1, 等. ABox推理计算实体相似度[J]. 西安交通大学学报, 2015,49(9):70-76. DOI： 10.7652/xjtuxb201509013.

Measuring Similarity of Entities Based on ABox Reasoning[J]. 2015, 49(9): 70-76. DOI： 10.7652/xjtuxb201509013.

摘要

针对主题图本体映射中主题上下文语义不易确定

缺少分类信息

但有明确的结构语义特征的特点

提出了A-Sim主题图本体映射算法。首先对主题图中的主题进行分类

利用描述逻辑语言ALCIR

的表达能力

根据主题属性及关联关系建立各种能表达上下文语义信息的概念术语集

将主题图本体转换为断言集合; 其次在断言集合上进行多项式复杂度实例检测

记录模型构造过程中的个体

获得主题的上下文语义; 最后将上下文语义结合元素级概念相似度算法计算实体综合相似度

获得异构主题图实体间的实体映射关系。通过对主题图进行相似度计算实验

结果证明新算法对主题图实体相似度计算综合性能至少提升了14%。

Abstract

Aiming at the problems that the context semantics of concepts are hard to make sure in the ontology mapping of topic map

and that the topics are lack of classification information but have well-defined constructive semantic characters

an A-Sim algorithm for ontology mapping of topic maps is presented in this paper. At first

the topics in topic maps are classified using expression ability of description logic language ALCIR

; then the concept terminology box expressing various context semantics of concepts is built according to the attributes and associations of topics

and the topic map ontologies are transformed into an assertions box. Second

a polynomial complexity algorithm for instance detection is presented and implemented on the assertions box

to obtain the context semantics of concepts by storing individuals in the process of

constructing models. At last

the semantic similarity which combines the syntax-based and semantic similarity measurements is measured to calculate the synthetic similarity of entities

and then the mapping relationship between entities of heterogeneous topic maps is obtained. The experiments of similarity measurement of topic maps demonstrated that the novel method has achieved better performance and improved the comprehensive performance value at least 14% than other methods.

关键词

Keywords

references

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MALCHER L, WITSCHEL H F. Merging of distributed topic maps based on the subject identity measure(SIM)approach [M]. Leipzig, Germany: LIT, 2004: 1-11.

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薛咏, 冯博琴, 刘伟涛. 扩展主题图本体融合策略与算法 [J]. 西安交通大学学报, 2011, 45(10): 13-18.

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GIUNCHIGLIA F, SHVAIKO P, YATSKEVICH M. S-Match: an algorithm and an implementation of semantic matching [C]∥ESWS. Berlin, Germany: Springer, 2004: 61-75.

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FOKOUE A, KERSHENBAUM A, MA L, et al. The summary abox: cutting ontologies down to size [M]. Berlin, germany: Springer, 2006: 343-356.

HAARSLEV V, MÖLLER R. Expressive Abox reasoning with number restrictions, role hierarchies, and transitively closed roles [C]∥International Conference on Principles of Knowledge Representation and Reasoning. Hamburg, Germany: Universität Hamburg, 2000: 273-284.

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