Approximations in Database Systems
Approximations in Database Systems
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DOI：
10.1007/3-540-36285-1_2
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发表时间：
2003-01
期刊：
影响因子：
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通讯作者：
Y. Ioannidis
中科院分区：
文献类型：
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作者：
Y. Ioannidis
对信息近似值的需要在最近的过去变得非常关键。从传统的查询优化到用户反馈和知识发现等新功能，数据管理系统需要快速交付近似数据，以满足其目标。已经提出了几种技术来解决这个问题，每种技术都有自己的优点和缺点。在本文中，我们来看看一些最重要的数据近似问题，并试图把它们放在一个共同的框架，并确定它们的相似性和差异。然后，我们暗示了一些开放的和具有挑战性的问题，我们认为值得调查。
The need for approximations of information has become very critical in the recent past. From traditional query optimization to newer functionality like user feedback and knowledge discovery, data management systems require quick delivery of approximate data in order to serve their goals. There are several techniques that have been proposed to solve the problem, each with its own strengths and weaknesses. In this paper, we take a look at some of the most important data approximation problems and attempt to put them in a common framework and identify their similarities and differences. We then hint on some open and challenging problems that we believe are worth investigating.