数据立方

它负责将数据立方定义组织成DMOLAP元数据。

It organizes data cube definition into DM_OLAP metadata .

通过一个高校学生信息系统的实际例子，对经由数据立方和MDX语言对有效计算频繁维谓词集的方法进行了有意的探索。

In the paper , we explore a helpful means to obtain multidimensional verb sets with data cube tool and MDX language through an example in students information system .

本文是对基于XML的数据立方数据模型的面向对象的实现。

This paper focuses on extending XML-based data cube with Oriented-object techniques .

基于XML数据立方的面向对象扩展

Oriented-object for XML-based Data Cube

数据立方计算及其在OLAPMINING中的应用

Efficient Data-Cube Computation and Application in OLAP MINING

MSOLAP数据立方自动增量更新的程序实现

Programming of Automatic and Incremental Update of Data Cube in MS OLAP

Dwarf数据立方是一种高度的压缩结构，同时保持CUBE的语义，使OLAP查询易于实现。

Dwarf is a highly compressed structure with OLAP semantic held .

汇总表就像数据立方（datacube），数据立方本质上是创建汇总表的独立软件产品或技术。

Summary tables are like data cubes , and a cube is basically a separate software product or technology that creates summary tables .

我们描述了OLAP应用的基本逻辑模型，并对多维数据立方提出了若干设想。

In this paper , we describe the basic logical models for OLAP applications , and present different proposals for multidimensional data cubes .

但现行的OLAP系统都没有充分利用大容量RAM，鉴于此，文章提出一种基于内存的数据立方查询处理系统。

But the existing OLAP systems don 't make full use of large size RAM , so a cube query in main memory system is proposed here .

在此基础上提出了基于浓缩数据立方的梯度联机挖掘MCGOBC算法。

The algorithm of mining cube gradient online based on condensed cube , MCGOBC is proposed .

这些多维的OLAP产品，即MOLAP产品，运行速度通常比其他方法更快，这是因为能直接把索引做进数据立方的结构，方便收集数据子集。

These multidimensional OLAP , or MOLAP , products typically run faster than other approaches , primarily because it 's possible to index directly into the data cube 's structure to collect subsets of data .

稀疏数据立方的一种快速计算方法

A Kind of Fast Calculating Method of Sparse Data Cube

dmGQL：一种新的数据立方梯度查询语言

DmGQL : A New Query Language of Cube Gradient

数据立方计算是代价非常大的操作，并且被广泛研究。

Data cube computation is a well-known expensive operation and has been studied extensively .

数据立方的计算在数据仓库中是非常必要但代价很大的操作。

The computation of data CUBE is necessary but high cost in data warehouse .

基于浓缩数据立方的内存实化小方的动态选择

Dynamic Main-memory Materialized Cuboids Selection in Condensed Cube

不完整数据立方的自底向上计算

Bottom - up Computation for Partial Data Cube

一种数据立方查询条件优化策略

An Optimization for Data Cube Query Expression

一种计算部分数据立方的算法

An Algorithm for Computing Partial Data Cube

数据立方梯度挖掘的研究

The Research of the Cube Gradient Mining

一种高度浓缩和语义保持的数据立方

A Highly Condensed and Semantics-Preserving Data Cube

动态数据立方的范围查询

Range Queries Technology on Data Cubes

基于内存的数据立方查询处理

Data Cube Query in Main Memory

有效的数据立方计算成为研究的热点之一。

It is becoming one of the research focuses to compute data CUBE efficiency in data warehouse .

研究了浓缩数据立方中约束数据立方梯度的挖掘问题。

In this paper , the problem of the mining constrained cube gradient for a condensed cube is studied .

由于数据立方的巨大尺寸，使其响应查询变慢。

Due to the enormous size of the data cube , the response of a query is slowed down .

为了从根本上解决这些问题，需要探索有效的数据立方计算和组织方法。

To solve these problems from the root , it is exigent to explore efficient data cube computation methods and cube storage structures .

将梯度挖掘与联机分析处理集成，也符合用户在浏览数据立方时产生的挖掘兴趣。

That the mining of cube gradient is integrated into online analytical processing also accords with users ' interest arising when browsing the data cube .

前缀立方在浓缩数据立方的基础上利用前缀共享和基本单元组技术有效地缩小了数据立方的尺寸。

Prefix Cube based on condensed cube was proposed to reduce the size of data cube more efficiently by augmenting BST condensing with prefix - sharing .