Deploy the association rule mining flow as a DB2 stored procedure.
将关联规则挖掘流部署为DB 2存储过程。
Create a Cognos report using results from dynamic association rule mining.
使用来自动态关联规则挖掘的结果创建一个Cognos报告。
First, learn about the task of association rule mining and how to achieve it in InfoSphere Warehouse.
首先，我们先来了解关联规则挖掘的任务以及如何在InfoSphere Warehouse内实现此任务。
To create the association rule mining model and extract the rules to a database table, do the following
要创建关联规则挖掘模型并将这些规则提取到数据库表，可以执行如下操作
Note, now the association rule mining flow is executing and returning the extracted rules to Framework Manager.
现在，关联规则挖掘流被执行并将所提取的规则返回给Framework Manager。
This paper presents an improved multi-level association rule mining algorithm.
为此，提出一种改进的多层关联规则挖掘算法。
Applying association rule mining to CRM can deepen the analytic function of CRM.
将关联规则应用于客户关系管理，深化CRM的分析功能。
Association rule mining is one of the most widely studied topics in the field of data mining.
关联规则挖掘是目前数据挖掘领域中研究最为广泛的课题之一。
Access frequency of database is one of the key factors to affect association rule mining performance.
数据库的访问频度是影响关联规则挖掘性能的关键因素之一。
Association rule mining which is a method of data mining reveals the latent information and knowledge.
作为一种数据挖掘的方法，关联规则揭示了数据中隐藏的信息和知识。
It applies classification rule mining, clustering rule and outlier mining to the management of Audit Risk.
一种新的抽样方法是把数据挖掘技术中的分类、聚类及离群点挖掘等应用到审计风险管理中去。
Feature association rule mining is filtering and finding characteristic patterns between object and background.
特征关联就是从复杂背景中筛选与发现目标特征，揭示目标与背景之间的特征模式。
In this article you learned about association rule mining and how to find association rules with InfoSphere Warehouse.
在本文中，您了解了关联规则挖掘及如何用InfoSphere Warehouse获得关联规则的有关内容。
Association rule mining is invoked by calling a stored procedure as all other mining operations in InfoSphere Warehouse.
对关联规则挖掘的调用是通过调用一个存储过程完成的，与InfoSphere Warehouse内的所有其他挖掘操作无异。
The paper presents the application of association rule mining in analyzing techniques and tactics of table tennis match.
介绍关联规则挖掘技术在乒乓球比赛技战术分析中的应用。
In this article, we discussed an analysis method of library 's hook circulation data, the association rule mining method.
本文探讨了图书流通数据的一种量化分析方法-关联规则的挖掘。
The system gives two kinds of recommendation algorithms based on association rule mining and user's transaction pattern clustering.
本系统给出了基于关联规则挖掘和基于用户事务模式聚类两种推荐算法。
Association rule mining is a highly interactive task, and users usually have to try many different parameter Settings to achieve the desired result.
关联规则挖掘是一项高度交互的任务，用户通常需要尝试多种参数设置才能达到理想的结果。
Association rule mining algorithm is used for discovering association rules, and much research was carried out by many researchers and scholars.
关联规则挖掘算法用于发现关联规则，诸多的研究人员和学者对其进行了大量的研究。
As the main research content of data mining, association rule mining is to find the hidden links or relevance from a large number of data items.
关联规则挖掘是数据挖掘的主要研究内容，它从大量的数据项中寻找隐藏着的联系或相关性。
Association rule mining is one of major research directions in data mining and has tremendous applications in business, science and other domains.
关联规则是其中一个主要的研究方向，有着广泛的应用价值。
The experimental results show that this new algorithm has proven its significant performance in the sparse multidimensional association rule mining.
实验结果表明，新算法在对具有稀疏特性的多维关联规则的挖掘中体现了良好的性能。
Rule clustering re-organizes rules which are generated during the procedure of association rule mining, to help customers find out interested rules.
规则聚类将关联规则挖掘产生的大量规则重新组织，帮助用户发现感兴趣的规则。
Association rule mining is an important sub-branch of the data mining, which mines interesting association relationships among a large set of data items.
关联规则挖掘作为数据挖掘领域的一个重要研究分支，它的任务是发现所有满足支持度阈值和置信度阈值的强关联规则。
Finally the problems in applying the MADSPM model to association rule mining in stream data are discussed and the strategies for solving them are also given.
最后对基于MADSPM模型的流数据关联规则挖掘问题中需注意的一些问题进行了阐述与分析。
Association rule mining is an important sub-branch of data mining. It has been used widely in selective marketing, telecom business, bank management and so on.
关联规则挖掘是数据挖掘的一个重要分支，并被广泛应用于市场营销、电信、银行等应用领域。
This article introduced the framework of the system, and particularly introduced the method of the correlative rule mining by taking image data as representative.
介绍了多媒体数据挖掘的系统结构，及以图像数据为代表的关联规则挖掘方法。
Using association rule mining can find the association from huge amount of data in business or other filed. It provides the important information to decision-making.
关联规则挖掘应用于商业等领域，它能发现大量数据中的关联关系，为制定决策提供重要信息。
Using association rule mining can find the association from huge amount of data in business or other filed. It provides the important information to decision-making.
关联规则挖掘应用于商业等领域，它能发现大量数据中的关联关系，为制定决策提供重要信息。
应用推荐