半结构化概率数据库

Alex Dekhtyar, J. Goldsmith, Sean R. Hawkes
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引用次数: 24

摘要

本文描述了一种新的统一存储和管理各种概率信息的理论框架。半结构化数据模型作为一种缺乏严格模式结构的数据表示方法,最近得到了广泛的接受。特别是,半结构化数据模型与可扩展标记语言(eXtensible Markup Language, XML)的底层数据模型的相似性,使得我们选择这种方法具有吸引力。XML是Internet上用于数据存储和传输的新兴开放标准。提出了半结构化概率对象的形式化模型。它们为存储和管理半结构化概率对象提供了理论基础。在此之前(S. Hawkes和A. Dekhtyar, 2001),我们开始了将该模型转换为XML的过程。介绍了建议的应用,给出了半结构化概率对象的形式化定义。最后,我们介绍了半结构化概率数据库的基础代数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semistructured probabilistic databases
The article describes a novel theoretical framework for uniform storage and management of diverse probabilistic information. The semistructured data model has gained wide acceptance recently as a means of representing data which lacks a rigid structure of schema. In particular, the similarity of the semistructured data model and the underlying data model for eXtensible Markup Language (XML), the emerging open standard for data storage and transmission over the Internet, make our choice of this approach attractive. The authors present the formal model for semistructured probabilistic objects. They provide the theoretical foundations for storing and managing semistructured probabilistic objects. Previously (S. Hawkes and A. Dekhtyar, 2001), we started the process of translating this model into XML. We introduce the advising application and give formal definitions of semistructured probabilistic objects. Finally, we introduce the underlying algebra for semistructured probabilistic databases.
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