Ontology-based semantic information integration resolves the schema level heterogeneity and part of data level heterogeneity between distributed data sources.
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）。
After all, SOA works well with other architectures, and SOA by itself doesn't solve information and semantic integration challenges.
毕竟，SOA能很好地与其他体系结构并存，而SOA本身并不能解决信息和语义集成挑战。
There are three major information integration patterns to achieve semantic interoperability: data federation, data consolidation and Enterprise Application Integration (EAI).
有三种主要的信息集成模式可用于实现语义互操作性：数据联合、数据整合和企业应用集成（EAI）。
In a broader sense, most information integration deals with semantic interoperability.
广而言之，大多数信息集成都是对语义互操作性进行处理。
This paper sets out to study the semantic problems in information organization. It expatiates on how to mediate semantic conflicts during information integration.
论文研究信息组织的语义问题，重点介绍了信息集成中语义一致性问题的解决。
The paper takes semantic integration in information query as an example to propose an improved semantic consistence maintenance model.
论文以信息查询中的语义集成为例，提出一个改进的信息语义维护模型。
Ontology technique resolves the problems of semantic heterogeneity in information integration which realizes the semantic interoperability between information systems.
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。
The proposed WWW information search engine service based on semantic classification is a meaningful try for us to achieve intelligentized information integration.
基于分类语义的WWW信息服务的搜索引擎系统的提出，对于在目前的情况下，如何实现智能化信息搜索服务，是一次有益的尝试。
In the process of information integration, ontology solved the semantic heterogeneity problem of heterogeneous and autonomous data.
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。
Semantic mapping is a fundamental problem for information integration.
语义映射是数据交换，信息集成的重要基础。
Semantic mapping is a fundamental problem for information integration.
语义映射是数据交换，信息集成的重要基础。
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