首页> 中文期刊> 《小型微型计算机系统》 >一种基于社会选择的本体聚类与合并机制

一种基于社会选择的本体聚类与合并机制

         

摘要

语义web为网页扩展了计算机可理解的、可处理的语义信息,然而由于本体数量激增导致的异构本体现象阻碍了语义的通信与融合.本体合并是解决本体异构的有效途径之一,旨将多个由agent构建的异构源本体通过本体合并机制形成一个共享的顶层本体,以期形成一个更大的语义共享空间.本文将本体合并看作是社会选择的一种应用,用于分析个体源本体与决策共享本体之间的关系.由于构建者的背景知识和推理能力不同会对合并结果产生影响,因此本文综合考虑源本体的可信度和一致赞同属性,设计了包含本体聚类器和本体聚集器的本体合并机制.首先,以社会选择和描述逻辑为基础构建本体合并框架和具体流程;在此基础上设计了基于距离的本体聚类算法,以减少不可信本体对合并结果的不利影响;接着对社会选择中的聚集函数进行总结和改进,并将其应用在本体合并中,介绍了积分聚集规则和阶梯性聚集规则.最后,本文对本体聚集规则的一致赞同属性做出分析,并通过对比实验验证了本体合并机制的有效性.%The semantic web extends computer understandable and processing semantic information for web pages,however the phe-nomenon of heterogeneous ontology caused by the multiplication of ontologies in the same domain has hindered semantic communica-tion and fusion. Ontology merging is an effective solution to ontology heterogeneity in semantic web which focuses on merging a group of individual local ontologies with distinct sources as a shared collective ontology to form a larger semantic shared space. We can view the ontology merging as the problem of social choice such as voting theory and judgement aggregation,analyzing the relationship be-tween the individual local ontology and shared collective ontology. The collective ontology will be affected by diverse background knowledge and reasonable abilities that different ontology builders has. Therefore,in this paper we consider the reliability as well as u-nanimity,and propose the ontology merging mechanism that includes ontology clustering and ontology aggregation. We firstly describe the framework and steps of ontology merging based on description logic,and design the distance-based ontology clustering to reduce the negative impact of unreliable ontologies. Then we summarize and improve the aggregation functions,apply aggregation rules to on-tology merging and present the scoring aggregation rule as well as staged-elimination rule. Finally,we study the unanimity of aggrega-tion rules and verify the effectiveness of ontology merging mechanism by experimental comparison results.

著录项

相似文献

  • 中文文献
  • 外文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号