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Indexing Dataspaces

机译:索引数据空间

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Dataspaces are collections of heterogeneous and partially unstructured data. Unlike data-integration systems that also offer uniform access to heterogeneous data sources, datas- paces do not assume that all the semantic relationships be- tween sources are known and specified. Much of the user interaction with dataspaces involves exploring the data, and users do not have a single schema to which they can pose queries. Consequently, it is important that queries are al- lowed to specify varying degrees of structure, spanning key- word queries to more structure-aware queries. This paper considers indexing support for queries that combine keywords and structure. We describe several exten- sions to inverted lists to capture structure when it is present. In particular, our extensions incorporate attribute labels, relationships between data items, hierarchies of schema ele- ments, and synonyms among schema elements. We describe experiments showing that our indexing techniques improve query effciency by an order of magnitude compared with alternative approaches, and scale well with the size of the data.
机译:DataSpaces是异构和部分非结构化数据的集合。与还提供统一访问异构数据源的数据集成系统不同,数据步骤不认为源的所有语义关系是已知的和指定的。与DataSpaces的大部分用户互动涉及探索数据,用户没有单个架构,它们可以姿势姿势查询。因此,重要的是,查询是为了指定不同程度的结构,跨越键词查询到更多的结构感知查询。本文考虑了组合关键字和结构的查询的索引支持。我们在存在时将多个延伸列表倒置列表以捕获结构。特别是,我们的扩展内容包含属性标签,数据项之间的关系,模式单元的层次结构,以及架构元素之间的同义词。我们描述了表明我们的索引技术通过替代方法比较的级别提高了查询效率,并使用数据的大小展现得很好。

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