联机分析挖掘系统是由事务驱动的，事务的优化能提高系统性能。
On Line Analytical Mining system is driven by transaction, so the optimization of transaction can improve system performance.
在数据库中实现联机分析挖掘模型需要实现联机分析处理和主动增量挖掘。
In order to implement the on-line analytical mining model, the on-line analytical processing and the active incremental mining need to be implemented in the database.
联机分析挖掘技术融合了联机分析处理技术和数据挖掘技术，成为决策支持应用系统新的技术依托。
The idea of using on-line analytical processing (OLAP) to access and analyze on-line monitoring data is presented.
关联规则分析是联机分析挖掘研究的一个重要内容，其目的是找出给定的数据集中的项之间有意义的联系。
Association rules mining is one of the important functions of data mining, which discovers a set of interesting association from relevant sets of data in a database.
在研究了联机分析处理与数据挖掘集成的联机分析挖掘系统基础上，设计了基于达梦联机分析处理服务器的数据立方梯度联机挖掘工具DM_MCGOBC。
After the online analytical mining model is studied, an online cube gradient mining tool DM_MCGOBC is designed based on the online analytical processing server DM_OLAP.
该提供者实现了OLE DB的规范，以及联机分析处理(OLAP)和数据挖掘的扩展规范。
This provider implements both the OLE DB specification and the specification's extensions for online analytical processing (OLAP) and data mining.
笔者对涉及到税务支持的几个关键问题进行了理论探讨和实际应用，包括数据仓库（DW）的建立和组织、联机分析（OLAP）和数据挖掘（DM）。
Several issues related with Tax decision making are studied and applied, including data warehouse(DW), online analyses and processing (OLAP) and data mining (DM).
本文以数据仓库为基础，与目前流行的联机分析处理、数据挖掘等技术相结合，提出了基于此的决策支持系统的设计。
Take data warehouse as foundation, with the aid of on Line Analytical Processing and data Mining technology, the composition and design of enterprise Decision Support System are put forward.
文中详细介绍了客户关系管理系统、数据仓库、联机分析处理和数据挖掘技术。
The CRM system, the Data warehouse, the OLAP (online analysis processing) and the technology of Data Mining are introduced in detail in the paper.
分析和论述了数据挖掘和联机分析处理的一般过程以及与此相关的一些技术。
Through analyze the general procedure of dada mining, OLAP and some other technique about them.
从数据的观点出发，讨论了数据驱动的决策支持系统的概念及其内涵，对数据仓库、联机分析处理和数据挖掘等手段也进行了一定程度的讨论。
From the point of view of data, this article discusses the concept of data driven decision support system, its connotation, as well as data warehouse, on line Analytical Processing and data mining.
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.
本文给出了基于数据仓库的矿山企业DSS框架结构，对数据仓库、联机分析与数据挖掘系统构建中的问题进行了探讨。
After introducing the main framework, certain key points of the system are discussed in detail such as the building of data warehouse, online analysis system and data mining system.
而基于这些系统数据信息基础之上建立的数据仓库以及联机分析和数据挖掘技术的应用，能够很好的解决以上的问题。
The data warehouse, OLAP and data mining technologies, which are based on data from above information systems, are good ways to solve these problems.
在商务智能系统中，联机分析处理和数据挖掘是针对商业数据的分析工具。
OLAP and DM are analytical tools aiming at business data in the business intelligence system.
主要谈到的是数据仓库和数据集市、联机分析处理和数据挖掘以及前端展示技术。
The ones that spoke of mainly are data warehouse and the data mart, OLAP and data mining, and show technologies in the front-ends.
本文以华侨大学为例，主要研究构建教学质量监控系统数据仓库所涉及的联机分析与数据挖掘技术。
At present, the keystone in education domain is how to develop the data warehouse of teaching quality monitor system(TQMS), and mine some data cubes about teaching subject for rules.
数据仓库直接为联机分析处理和数据挖掘提供数据源。
商业智能的支撑技术包括数据仓库、联机分析处理和数据挖掘。
Data Warehouse, Online Analytical Processing and Data Mining constitute the supporting technology for BI.
本文主要利用数据仓库、联机分析处理技术和数据挖掘等多种技术构建潍坊网通的分析CRM系统，即经营分析管理子系统。
The paper introduces how to construct the Business analysis management in CRM by applying the Data Warehouse, On-Line Analytical Processing and Data Mining.
摘要：在介绍了商业智能的核心技术和体系结构包括数据仓库、联机分析处理、数据挖掘等的基础上。
Absrtact: Introduces the main technology and system structure of business intelligence including data warehouse (DW), OLAP and data mining.
目前的商务智能系统主要包括数据收集、数据仓库、数据挖掘和OLAP联机分析四个部分。
Currently the Business Intelligent System includes four parts, which are Data Collection, Data Warehouse, Data Mining and OLAP.
伴随数据仓库技术出现的数据挖掘技术和联机分析处理OLAP技术又为数据分析提供了强有力的支持。
With the emergence of data warehouse, data mining technology and OLAP technology also come out. These two technologies provide the powerful support for data analysis.
论文的主要工作如下：（1）对决策支持系统、数据仓库、联机处理分析OLAP、数据挖掘相关理论和技术进行了研究。
The paper's main tasks are as follows:(1) Some research was developed which was about the theory and technology of DSS, data warehouse (DW), Online Analytical Processing ( OLAP ) , data mining(DM).
为了实现联机分析处理和数据挖掘的紧密结合，我们提出在多维数据模式的基础上同时支持OLAP应用和数据挖掘应用的思路。
In order to support the applications of OLAP and data mining simultaneously, we gave the orientation that the multidimensional data model become the common data basic of OLAP and data mining,.
为了实现联机分析处理和数据挖掘的紧密结合，我们提出在多维数据模式的基础上同时支持OLAP应用和数据挖掘应用的思路。
In order to support the applications of OLAP and data mining simultaneously, we gave the orientation that the multidimensional data model become the common data basic of OLAP and data mining,.
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