凸立方体
Cubes convexes
摘要：
在各种方法中，数据立方体是预先计算的，以便有效地回答OLAP查询。数据立方体的概念已经以各种方式被削弱：冰山立方体，范围立方体或差分立方体。在本文中，我们引入了凸立方体的概念，它捕获所有元组的数据立方体满足约束组合。它可以以非常紧凑的方式表示，以优化计算时间和所需的存储空间。凸立方体不是附加到立方体变体列表的附加结构，但我们提出它作为一个统一的结构，我们使用它来表征，在一个简单的，健全的和均匀的方式，其他引用类型的立方体。最后，我们介绍了新兴立方体的概念，它捕捉了显着的趋势反转。特征化。
英文摘要：
In various approaches, data cubes are pre-computed in order to answer efficiently OLAP queries. The notion of data cube has been declined in various ways: iceberg cubes, range cubes or differential cubes. In this paper, we introduce the concept of convex cube which captures all the tuples of a datacube satisfying a constraint combination. It can be represented in a very compact way in order to optimize both computation time and required storage space. The convex cube is not an additional structure appended to the list of cube variants but we propose it as a unifying structure that we use to characterize, in a simple, sound and homogeneous way, the other quoted types of cubes. Finally, we introduce the concept of emerging cube which captures the significant trend inversions. characterizations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
