Reconciling Semantic Heterogeneity by Leveraging Past Experience
Reconciling Semantic Heterogeneity by Leveraging Past Experience
批准号:
0415175
负责人:
Dan Suciu
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-09-01 至 2009-08-31
中文摘要
本研究项目的目标是开发弥合语义异构性的方法。语义异构性出现在需要在多个数据源和应用程序之间共享数据的上下文中,并且这些源使用不同的术语。例如,公司拥有大量数据库,需要在这些数据库之间进行协调,以利用它们的价值。同样,大型科学项目和政府机构之间的协调也需要在多个存储库之间共享数据。该方法包括收集特定领域中的大量模式,并尝试了解数据库设计人员在该领域中使用的模式及其变体。通过利用这些模式,可以在域中以前未见的数据库模式之间进行匹配。通过开发不同模式之间的匹配系统,并将这些技术应用于搜索当今万维网上可用的越来越多的Web服务,这些技术得到了验证。这项研究正在构建的系统之一是一个Web服务搜索引擎,它试图获取Web服务操作的潜在含义,并将从华盛顿大学(http://data.cs.washington.edu/schemaMatching/index.htm).获得该项目的成果将提供一套在线服务以及可供研究界使用的公共数据集。这项研究可能的直接应用包括生物医学信息学和深度网络搜索。结果是
英文摘要
The goal of this research project is to develop methods for bridging semantic heterogeneity. Semantic heterogeneity arises in contexts where data needs to be shared among multiple data sources and applications, and these sources use different terminologies. For example, companies own a large number of databases, and need to coordinate between them in order to leverage their value. Similarly, large-scale scientific projects and coordination among government agencies also requires sharing data across multiple repositories. The approach consists of collecting a large number of schemas in a particular domain and trying to learn the patterns and variations on patterns that database designers use in the domain. By leveraging such patterns, it is possible to match between previously unseen database schemata in the domain. The techniques are validated by developing systems for matching between disparate schemata, and by applying the techniques to searching the growing number of web-services available today on the World Wide Web. One of the systems being built by this research is a search engine for web services that attempts to get at the underlying meaning of the web-service operations and will be available from the University of Washington (http://data.cs.washington.edu/schemaMatching/index.htm). The results of the project will provide a set of online services as well as public data sets that can be used by the research community. Possible direct applications of this research include biomedical informatics and deep-web search. The results
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会议论文
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