数据的不确定性和谱系研究

Lu Peng
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引用次数: 0

摘要

近年来,数据量呈指数级增长,由此带来的数据不确定性越来越普遍,这是不争的事实,给我们的生活和科学研究带来了许多负面影响。通过近十年的研究,Trio团队开发了一个相对成熟的系统原型Trio来演示他们对不确定数据的解决方案并从理论上进行了论证。Trio系统补充和扩展了传统的关系数据库。为了继承关系数据库的诸多优点,提出了一种改进的ULDB数据模型和相应的面向不确定数据库的TriQL查询语言。本文研究了大量斯坦福大学Trio项目的相关资料,主要做了以下工作:对复杂的Trio系统中的逻辑关系进行分析和组织,使读者以简单的方式更清楚地了解自己的提案;2. 分析比较具有不确定性的传统数据库和扩展数据库的数据模型和查询实现;此外,本文还简化了复杂Trio系统的工作原理和实现,为进一步研究提供了便利和参考,为当前不确定数据领域的研究提供了新的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Data Uncertainty and Lineage Through Trio
It is an indisputable fact that the amount of data has grown exponentially, and the resulting uncertainty of data has become more and more common in recent years, which has brought many negative effects to our life and scientific research. Through nearly a decade of research, the Trio team developed a relatively mature system prototype Trio to demonstrate their solutions to uncertain data and theoretically demonstrated. The Trio system supplements and expands the traditional relational database. In order to inherit the many advantages of the relational database, an improved ULDB data model and corresponding TriQL query language for uncertain databases are proposed. Studying a lot of Stanford's Trio project related materials, this article has mainly done the following work: 1. Analyze and organize the logical relationships in the complex Trio system, so that readers have a clearer understanding of their proposals in a simple way; 2. Analyze and compare the data model and query implementation between traditional database and extended database with uncertainty; In addition, the paper also simplifies the working principle and implementation of the complex Trio system, provides convenience and reference for further research, and provides a new perspective for the current research in the field of uncertain data.
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