XStruct: Efficient Schema Extraction from Multiple and Large XML Documents

J. Hegewald, Felix Naumann, Melanie Herschel
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引用次数: 80

Abstract

XML is the de facto standard format for data exchange on the Web. While it is fairly simple to generate XML data, it is a complex task to design a schema and then guarantee that the generated data is valid according to that schema. As a consequence much XML data does not have a schema or is not accompanied by its schema. In order to gain the benefits of having a schema - efficient querying and storage of XML data, semantic verification, data integration, etc.- this schema must be extracted. In this paper we present an automatic technique, XStruct, for XML Schema extraction. Based on ideas of [5], XStruct extracts a schema for XML data by applying several heuristics to deduce regular expressions that are 1-unambiguous and describe each element’s contents correctly but generalized to a reasonable degree. Our approach features several advantages over known techniques: XStruct scales to very large documents (beyond 1GB) both in time and memory consumption; it is able to extract a general, complete, correct, minimal, and understandable schema for multiple documents; it detects datatypes and attributes. Experiments confirm these features and properties.
XStruct:从多个大型XML文档中高效提取模式
XML实际上是Web上数据交换的标准格式。虽然生成XML数据相当简单,但是设计一个模式并保证根据该模式生成的数据是有效的,这是一项复杂的任务。因此,许多XML数据没有模式,或者没有模式。为了获得拥有模式的好处——XML数据的高效查询和存储、语义验证、数据集成等——必须提取该模式。在本文中,我们提出了一种用于XML模式提取的自动技术XStruct。基于[5]的思想,XStruct通过应用几种启发式方法来推导正则表达式来提取XML数据的模式,这些正则表达式是1-明确的,并且正确地描述了每个元素的内容,但是泛化到一个合理的程度。与已知技术相比,我们的方法有几个优点:XStruct在时间和内存消耗方面都可以扩展到非常大的文档(超过1GB);它能够为多个文档提取一个通用的、完整的、正确的、最小的和可理解的模式;它检测数据类型和属性。实验证实了这些特征和性质。
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