一种基于本体的多源遥感数据集成系统

文章针对多源遥感数据集成共享的需求,分析了遥感数据源存在的数据冲突,提出了一种基于本体的遥感数据集成模型。通过OWL表示本体和映射关系,实现全局遥感数据本体与局部数据本体的冲突消解。     

数据交换中基于本体的语义冲突消解方案

为解决数据交换过程中的语义冲突问题,提出一种基于本体的语义冲突消解方案。利用ER模型实现关系模式到XML模式的语义映射,采用本体对经过初步语义转换的XML Schema进行语义标注。实验结果表明,该方案能减少由自然语言或符号不同引起的歧义,在一定程度上消除语义冲突。     

医学图像网格基于语义的信息集成方法

提出了一种医学图像网格MedImGrid(medical image grid)基于语义的信息集成方法.基于HL7 RIM(health level 7 referenced information model)生成父本体(HL7-RIM ontology),采用混合方式(hybrid means)建立MedImGrid全局和局部本体的分级结构.结合代理和中间件技术开发了HL7(health level 7) Grid中间件,实现了具有医疗语义解析功能的HL7智能代理,以支持对异构数据源的Grid Service封装与统一访问.基于本体标记表达异构数据模式的语义模型在本体层的相关关联,参照MedImGrid各级本体实现数据源间的语义解析和映射.MedImGrid原型系统基于CGSP2(China grid support platform v2.0),采用了局部与全局语义映射松耦合的构架,其特有的层次结构使得网格环境下跨系统/医院的信息集成更加有效.     

A philosophy‐driven entity classification and enrichment for ontology mapping

Abstract: Ontologies are intended to facilitate semantic interoperability among distributed and intelligent information systems. Because of the distributed nature of the World Wide Web, Web ontologies have been developing in multiple forms of heterogeneity. For interoperating among information systems through heterogeneous ontologies, ontology mapping is a prerequisite process to generate alignment between two ontologies. In order to improve alignment accuracy, our approach is to clarify and enrich the semantics of ontological entities before mapping. For this purpose, we present a semi‐automatic framework of entity classification and enrichment by applying three philosophical notions: identity condition, existential rigidity, and external dependency. Our objective is to supply a set of philosophy‐driven anchors into ontologies for their mapping process by using a sortal taxonomy as a background knowledge model.     

Semantic Ontology Mapping for Interoperability of Learning Resource Systems using a rule-based reasoning approach

There is an increasing demand for sharing learning resources between existing learning resource systems to support reusability, exchangeability, and adaptability. The learning resources need to be annotated with ontologies into learning objects that use different metadata standards. These ontologies have introduced the problems of semantic and structural heterogeneity. This research proposes a Semantic Ontology Mapping for Interoperability of Learning Resource Systems. To enable semantic ontology mapping, this research proposes conflict detection and resolution techniques for both semantic and structural conflicts. The Semantic Bridge Ontology has been proposed as a core component for generating mapping rules to reconcile terms defined in local ontologies into terms defined in the target common ontology. This work defines the reasoning rules to classify related learning objects to enhance the powerful deductive reasoning capabilities of the system. As a consequence, ontology-based learning object metadata are generated and used by the semantic query engine to facilitate user queries of learning objects across heterogeneous learning resource systems.     

Variable weight semantic graph‐based ontology mapping method

The mapping method that is based on the name and structure of the ontology elements is the strategy used in most mapping methods. Methods using the name often only use the similarity between the individual elements in the ontology to predict the semantic relations between two ontologies, while the latter measure the mapping between two ontologies by means of the structural relations between the elements. The effects of these two kinds of mapping strategies are not ideal. Addressing this issue, the work presented in this paper proposes an ontology mapping approach, in which the ontology element name and structure are combined. It uses the approaches based on linguistics and distance to generate a variable weight semantic graph. On this graph, the similarity of element names and structure are calculated through iterative computation. In the process of iteration, similarity result values are constantly adjusted. The approach avoids the problem of single methods that cannot use the entire amount of ontology information; therefore, it provides a more ideal mapping result. For making full use of the message of ontology, our implementation and experimental results are provided to demonstrate the effectiveness of the mapping approach.     

基于本体的异构数据集成框架

针对电力系统数据集成中存在的语义异构问题,提出一种基于本体的数据集成框架。依据电力参数估计系统的数据需求模型,分析数据集成存在的语义冲突类型,在传统数据集成框架的数据集成中间件模块中加入本体语义描述模块。采用本体描述信息资源域中的概念,通过实现语义冲突主动发现并构建语义映射关系。实验结果表明,该框架能有效解决数据集成过程中的语义异构问题。     

基于本体语义映射的数据集成机制研究

数据集成的难点是如何解决数据之间的语义异构问题,本文利用本体在语义集成上的优点,提出了一种基于本体语义映射的数据集成框架。根据本体概念的定义及其结构,给出了一种本体语义映射算法,该算法通过属性集合间的比较确定概念语义关系,在计算概念相似度时,考虑了概念名称、概念属性集合和相关概念的语义信息。最后通过概念的属性集映射算法和概念映射算法实现了本体语义映射,从而重点解决了数据集成中的语义映射问题。     

一种基于Ontology的数据集成系统

针对异构数据源中实现基于语义的数据集成的需求，采用分层思想，在用户层与实际数据层之间增加一个中间层来屏蔽底层数据的异构，用本体作为公共语义描述工具，建立本体到各数据源的映射规则，设计实现了将基于本体的全局查询转化为基于各数据源的局部查询系统，解决了数据源之间的语义异构问题，其中用OWL表示本体和映射，并研究了系统中的关键技术。     

基于语义的采油工程领域数据集成系统研究

针对采油工程领域海量、分布、异构的数据源,在构建领域全局语义模型的基础上,提出一套基于语义的采油工程领域数据集成系统(Oil Production Engineering Semantic-based Data Integration System, OPSDS)。该系统通过对领域数据模型进行本体抽取、本体演化、本体合并、约束推理,建立适合采油工程领域的全局语义数据模型,为用户和上层应用程序提供基于语义的数据服务。     

基于领域本体的语义标注方法研究

介绍了语义Web.本体以及语义标注的基本概念,对语义标注方法以及现有技术工具进行了简单地说明和分析,提出了一种基于领域本体的语义标注方法,并结合石油产品领域的本体对该方法进行了实例说明.该方法通过分析文档的特征词汇,使用基于领域本体的空间向量模型方法建立词汇与本体概念之间的映射.采用这种方法对文档进行语义标注后,可以把文档隐含的语义信息显式的表现出来,这样数据库内部文档之间就具有了语义关联关系,为检索的智能推理提供基础.     

PROMES: An ontology‐based messaging service for semantically interoperable information exchange during disaster response

Disaster response requires the cooperation of multiple emergency responder organizations (EROs). However, after‐action reports relating to large‐scale disasters identity communication difficulties among EROs as a major hindrance to collaboration. On the one hand, the use of two‐radio communication, based on multiple orthogonal frequencies and uneven coverage, has been shown to degrade inter‐organization communication. On the other hand, because they reflect different areas of expertise, EROs use differing terminologies, which are difficult to reconcile. These issues lead to ambiguities, misunderstandings, and inefficient exchange of data and information among those involved, which can impede the response process and slow decision making. We, therefore, hypothesize that promoting semantic interoperability across ERO information systems might improve information exchange among stakeholders and thereby allow a more coherent response to the disaster. We propose an ontology‐based messaging service on the basis of the Emergency Data Exchange Language (EDXL) standards. The parties involved will continue to use the terminologies to which they are accustomed, but the system will resolve inconsistencies and thereby enhance mutual understanding among EROs by ensuring semantic translation of the exchanged information. The evaluation of the semantic translation demonstrated the effectiveness and accuracy of the proposed service.     

一种概念本体的共享方案

针对不同知识系统概念和术语的不统一,讨论了应用领域知识系统在概念本体共享交换层的设计和实现,重点研究了本体在语法和语义上的异构性,提出了建立全局本体结合各本地本体系统的语义异构解决方案。在OIL对RDFS的扩展的基础上,依据框架概念本体表达的特点对RDFS进行了扩展补充,建立了概念本体与OIL及扩展RDF(S)语法的映射关系,确定了将概念本体转换为XML文本的方法。     

基于本体的语义查询优化

Web信息检索技术已经在全世界广泛应用,然而,搜索引擎的查全率和查准率却不能够令用户满意,因此提出了一种基于通用本体WordNet的语义层次结构.通过计算和分析查询关键字与本体库的映射达到查询优化的目的.该方法通过建立一个简单的语法树并且索引WordNet,对查询关键字词法特性和本体实例之间语义关联强弱进行扩展和分析,提高了查询关键字到本体概念映射的完整性和准确率,进而帮助搜索引擎对用户的意图作出有效推测.实验表明,该方法可以有效地优化查询.     

基于语义视图的SPARQL-SQL查询转换方法

针对油气井工程领域关系数据库,提出一种基于语义视图的SPARQL-SQL查询转换方法.该方法采用特定本体描述数据源关系模式,通过RDF三元组形式,将关系表定义为领域本体之上的语义查询视图,从而建立数据源与本体之间的映射关系,并根据语义映射信息,将提交的SPARQL语句进行解析与查询重写,转换为面向关系数据源的SQL语句.通过实现油气井虚拟数据中心,验证了该方法的可行性与有效性,并获得了良好的应用效果.     

一种面向语义网服务的本体映射框架*

本体的异构性阻碍了语义网服务的互操作。从解决语义网服务中本体的异构问题出发,同时考虑到目前的本体映射系统大多效率不高、映射结果不够准确的问题,提出了一种适用于语义网服务的本体映射方法及系统框架。该方法利用机器学习技术来提高本体映射的自动化程度,利用综合评判技术修正映射结果,以提高本体映射的准确率。采用OAEI 2007的基准测试数据集benchmarks进行实验测试,结果表明本系统的性能基本达到预期效果,能够有效地解决语义网服务中的本体异构问题。     

DW中一种基于本体的语义集成方法研究

文中介绍了数据仓库领域一种基于本体的语义集成方法。首先建立领域本体和数据源的局部本体,然后通过局部本体对应的概念树间的映射算法得到数据源全局本体,再和领域本体映射,得到映射关系。最后通过本体推理,得出隐含的语义关系,用最终的语义关系来指导数据抽取、转换和加载过程,实现数据仓库语义程度上的数据集成。     

基于领域本体和关系模型的XML语义集成方法研究

由于缺乏足够的语义信息,不同模式的XML数据之间很难进行互操作。针对油气井工程中的XML数据集成需求,借助领域全局本体,提出一种模式无关的XML语义集成方法。该方法首先在XML Path路径与领域本体之间进行语义映射,屏蔽其模式差异;然后,按照模型映射方法将XML存储为关系数据;最后通过查询重写将SPARQL转换为SQL语句,实现语义查询。该方法对XML模式进行语义标注,利用关系数据库存储与查询XML数据,能有效处理领域XML数据的语义集成。