本文基于本体来解决语义异构问题。
This paper is intended for the solution of heterogeneous semantics problems.
本体可以很好地解决异质数据源的语义异构问题。
Ontology plays an important role in solving the problem of semantic heterogeneity of heterogeneous data sources.
结合本体技术解决分布式异构数据集成中的语义异构问题。
Resolved the semantic heterogeneous problem in the distribution heterogeneous data integration, combining with ontology technology.
该文主要讨论集成过程中的异构问题，尤其是语义异构问题。
The paper discusses the heterogeneous problems in data integration, especially on the semantic heterogeneity.
有效的验证了基于服务的数据集成方法解决语义异构的可行性。
Validated the feasibility of settling semantic heterogeneous based on data integrating service method effectively.
实验结果表明，该方法可在一定程度上支持语义异构，提高匹配的准确度。
The experimental results show that the method supports different semantics to a certain extent, and improves the accuracy of matching.
主要目的是解决数据源的系统异构，模式异构，位置异构，以及部分语义异构问题。
This paper try to solve system heterogeneous, model heterogeneous, position heterogeneous and part of semantic heterogeneous.
本体技术解决了信息集成中的语义异构性问题，从而实现了信息系统间的语义互操作。
Ontology technique resolves the problems of semantic heterogeneity in information integration which realizes the semantic interoperability between information systems.
在信息集成过程中，本体解决了异构信息的语义异构问题，实现了信息语义上的互操作。
In the process of information integration, ontology solved the semantic heterogeneity problem of heterogeneous and autonomous data.
其中如何解决异构数据源之间存在的系统异构、语法异构和语义异构问题就成为一个非常重要的研究课题。
Therefore, how to resolve the system heterogeneity, syntax heterogeneity and semantic heterogeneity between data sources becomes a critical research subject.
进而对基于语义异构空间数据转换模型进行了深入地研究，从模型的定义、原理、组织构成进行了详细地阐述。
And then carry on deep research to Multi-source Spatial Data Translation model in semantic level and explain in detail to the definition, principle, organization of the model.
可互操作它们可以使用公共的行业语义集与异构的系统和技术进行互操作。
Interoperable They can interoperate with disparate systems and technologies using a common set of industry semantics.
语义冲突是基于不同信息源和信息结构上的异构软件集成所面临的主要问题之一。
Semantic conflicting is one of main problems that face integration of heterogeneous softwares based on different dada sources and structure .
许多应用要求对相关信息源进行综合查询，因此必须解决这些异构数据源的语义互操作。
Meanwhile, many applications require the integrated query from related information resources, which arises the problem of semantic interoperation in heterogeneous information resources.
为了更好地解决网格系统中的访问控制问题，本文从网格系统的动态性和异构性出发，提出了一种新的基于语义技术的网格访问控制方法。
To address this thesis, this paper focuses on the dynamic and heterogeneous characteristic of Grid, and presents a new access control method based on semantic technology.
本体映射是解决本体异构，在不同本体间建立语义关联的一种有效的方法。
Ontology mapping is an effective method of solving the heterogeneity of ontology and setting up semantic relevance.
基于本体的异构数据库的语义集成，首先就是要对本体进行构建。本体构建质量的高低直接影响了进一步的应用和研究效果。
The first step of Ontology-based semantic integration of heterogeneous database is to build ontology. The quality of ontology has a direct impact on further application and research.
基于本体的语义信息集成主要解决分布异构的数据源之间的模式级异构和部分数据异构（包括同义字和同音异义字）。
Ontology-based semantic information integration resolves the schema level heterogeneity and part of data level heterogeneity between distributed data sources.
本文提出了语义值的概念和用语义值来消除各异构数据库的语义差别，从而实现多个数据库互访的一种方法。
This paper presents a concept of semantic value and a method to implement the mutual visiting among multiple database using the semantic value to eliminate the semantic difference.
首先定义模型互操作的概念，分析异构模型互操作中存在的问题是不同的描述方式及不同的语义。
The analyses results show that the problems in the interoperation process of heterogeneous are different description manners and different semantemes.
分析当前的异构数据集成可以发现，如何更好地解决异构性和语义冲突至关重要。
From the analysis, we can see that it is important to resolve the heterogeneity and semantic conflict.
对于不同语义环境下的网络服务，也很难进行沟通，对异构数据也缺乏有效的映射及沟通手段。
For web services under different semantic environment, it is hard for them to communicate, and efficient mapping technology is still lack for communication of heterogenous data.
对于不同语义环境下的网络服务，也很难进行沟通，对异构数据也缺乏有效的映射及沟通手段。
For web services under different semantic environment, it is hard for them to communicate, and efficient mapping technology is still lack for communication of heterogenous data.
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