Uncertainty Annotated Databases - A Lightweight Approach for Approximating Certain Answers

Uncertainty Annotated Databases - A Lightweight Approach for Approximating Certain Answers
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不确定性注释数据库 - 近似某些答案的轻量级方法

DOI:
10.1145/3299869.3319887
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发表时间:
2019
期刊:
SIGMOD
影响因子:
--
通讯作者:
Kennedy, Oliver
Kennedy, Oliver
中科院分区:
--
文献类型:
--
作者:
Feng, Su;Huber, Aaron;Glavic, Boris;Kennedy, Oliver

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确定答案是处理许多实际数据管理任务中出现的不确定性的原则性方法。不幸的是,这种方法是昂贵的,并可能排除有用的(如果不确定)答案。因此,用户经常采取不太原则的方法来解决不确定性。在本文中,我们提出了不确定性注释数据库(UA-DBs),它结合了联合收割机的下和过近似的某些答案,以实现某些答案的可靠性,与一个经典的数据库系统的性能。此外,与先前对某些答案的研究相比,UA-DB通过包括一些不确定的(明确标记的)答案来实现更高的效用。UA-DB是基于不完整的K-关系,我们引入它来推广经典的基于集合的不完整数据库的概念和更大类的数据模型的某些答案。使用我们的方法的实现,我们证明了实验,它有效地产生紧密近似的某些答案是高实用性。
Certain answers are a principled method for coping with uncertainty that arises in many practical data management tasks. Unfortunately, this method is expensive and may ex- clude useful (if uncertain) answers. Thus, users frequently resort to less principled approaches to resolve uncertainty. In this paper, we propose Uncertainty Annotated Databases (UA-DBs), which combine an under- and over-approximation of certain answers to achieve the reliability of certain answers, with the performance of a classical database system. Furthermore, in contrast to prior work on certain answers, UA-DBs achieve a higher utility by including some (explicitly marked) answers that are not certain. UA-DBs are based on incomplete K-relations, which we introduce to generalize the classical set-based notion of incomplete databases and certain answers to a much larger class of data models. Using an implementation of our approach, we demonstrate experimentally that it efficiently produces tight approximations of certain answers that are of high utility.
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