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首页> 外文期刊>Arabian Journal for Science and Engineering >Bitmap Index in Ontology Mapping for Data Integration
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Bitmap Index in Ontology Mapping for Data Integration

机译：用于数据集成的本体映射中的位图索引

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摘要

Selecting a relevant data source among the available ones in a data integration system plays vital role in optimizing query performance. The sources are heterogeneous and autonomous and can join and leave an integration system arbitrarily. Some sources may not contribute significantly to a user query because they are not relevant to it. Executing a user query against all available sources consumes resources unreasonably and makes the query processing expensive. The existing techniques for source selection take significant time in traversing source descriptions. Consequently, query response time degrades in coping with the growing number of available sources. Semantic heterogeneities of data add further complexity to source selection. As a first step, we employed ontologies for identifying the relevant data elements of individual sources for particular queries and semantic relationships among these data elements. Then, we mapped local ontologies with domain ontology through a bitmap index. In spite of traversing the local ontologies, our proposed system utilizes the bitmap index to perform relevance reasoning in order to optimize the user query response. A prototype system has been designed and implemented to validate the system. We evaluated the prototype system for query response time and it was improved due to the incorporation of a bitmap index.
机译：在数据集成系统的可用数据源中选择相关的数据源在优化查询性能方面起着至关重要的作用。这些源是异构的并且是自治的，并且可以任意加入和离开集成系统。一些来源可能与用户查询无关，因为它们与查询无关。针对所有可用源执行用户查询会不合理地消耗资源，并使查询处理成本很高。现有的源选择技术在遍历源描述时会花费大量时间。因此，随着越来越多的可用资源，查询响应时间会降低。数据的语义异构性进一步增加了源选择的复杂性。第一步，我们使用本体来识别特定查询的单个来源的相关数据元素以及这些数据元素之间的语义关系。然后，我们通过位图索引将本地本体与域本体映射在一起。尽管遍历了本地本体，但我们提出的系统还是利用位图索引执行相关性推理，以优化用户查询响应。已经设计并实施了原型系统来验证系统。我们评估了原型系统的查询响应时间，并由于引入了位图索引而对其进行了改进。

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