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Querying Tree-Structured Data Using Dimension Graphs

机译:使用维图查询树形结构数据

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摘要

Tree structures provide a popular means to organize the information on the Web. Taxonomies of thematic categories, concept hierarchies, e-commerce product catalogs are examples of such structures. Querying multiple data sources that use tree structures to organize their data is a challenging issue due to name mismatches, structural differences and structural inconsistencies that occur in such structures, even for a single knowledge domain. In this paper, we present a method to query tree-structured data. We introduce dimensions which are sets of semantically related nodes in tree structures. Based on dimensions, we suggest dimension graphs. Dimension graphs can be automatically extracted from trees and abstract their structural information. They are semantically rich constructs that provide query guidance to pose and evaluate queries on trees. We design a query language to query tree-structured data. A key feature of this language is that queries are not restricted by the structure of the trees. We present a technique for evaluating queries and we provide necessary and sufficient conditions for checking query unsatisfiability. We also show how dimension graphs can be used to query multiple trees in the presence of structural differences and inconsistencies.
机译:树结构提供了一种流行的方法来组织Web上的信息。主题类别,概念层次结构,电子商务产品目录的分类法就是此类结构的示例。由于名称不匹配,结构差异和结构不一致(即使对于单个知识领域而言),查询使用树形结构组织其数据的多个数据源也是一个具有挑战性的问题。在本文中,我们提出了一种查询树状结构数据的方法。我们介绍维,它们是树结构中语义相关节点的集合。根据尺寸,我们建议尺寸图。可以从树中自动提取尺寸图并提取其结构信息。它们是语义丰富的构造,可提供查询指导以对树进行摆放和评估查询。我们设计一种查询语言来查询树状结构的数据。这种语言的一个关键特征是查询不受树结构的限制。我们提出了一种评估查询的技术,并为检查查询的不满足性提供了必要和充分的条件。我们还展示了在结构差异和不一致的情况下如何使用维度图查询多棵树。

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