You can express each rule found in the data mining as a merchandising association.
您可以将在数据挖掘中发现的每条规则表示成商品销售关联。
Association rule learning searches for relationships between data objects to make predictions, position products, and so on.
关联性规则学习(Association rule learning)搜寻数据对象之间的关系，以做出预言、定位产品，等等。
Secondly, it analyzed association rule and sequence mode used in the process of data mining and compared the main algorithms of association rule and sequence mode.
其次，分析了数据挖掘中所使用的关联规则和序列模式，对关联规则和序列模式的各种挖掘算法进行了比较。
A model of data mining is set up after preparation of data by means of attribute structure, and association rule algorithms are carried out. the data mining result is explained and analysed.
采用了属性构造法进行数据预处理，建立了数据挖掘模型，实现了关联规则算法，并对挖掘结果进行解释与分析。
Association rule is a method of data mining, whose typical application is the analysis of shopping basket in supermarket.
关联规则是数据挖掘的一种方法，它的最典型的应用是超市的购物篮分析。
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。
Several major kinds of data mining methods, including characterization, classification, association rule, clustering, outlier detection, pattern matching, data visualization, and so on.
常用的数据挖掘方法包括描述、分类、关联规则、聚类、孤立点检测、模式匹配、数据可视化等。
Association rule is one of the key technologies in data mining.
关联规则是数据挖掘的主要技术之一。
One resolution is that server predicts hot data with the rule discovered in association rule mining and USES data broadcasting technology to push hot data to mobile client.
一种解决方案是服务器根据关联规则挖掘出的规律，对热点数据进行预测，并利用数据广播技术将热点数据不断地推向移动客户机。
Data mining always faces complicated tasks that including classification, prediction, association rule discovering and clustering, etc.
数据挖掘面对的任务是复杂的，通常包括分类、预测、关联规则发现和聚类分析等。
Also, some of data mining algorithms that are commonly used in Web Usage mining are clustering, association rule generation, sequential pattern generation etc.
同时本篇论文也主要提出了一些经常被使用的数据挖掘的算法像聚类挖掘、关联规则挖掘、序列模式挖掘等。
Discovering association rules between items in a large database is an important data mining problem as the number of association rule is usually very larger.
在大型数据库项目之间发现关联规则是一个重要的数据挖掘问题，而挖掘出的关联规则数目常常是巨大的。
In particular, the class association rule (CAR), which can be used not only for concept description but also for class prediction and decision-making, has an important role in data mining.
特别是分类关联规则既能用于概念描述又能用于分类预测与决策，在数据挖掘中发挥重要作用。
This paper proposes a rule recycle technique, which reuses the rules deleted in previous data mining by reclaiming and composing them in order to obtain more association rules.
该文利用规则回收技术，以回收组合的方法将已往在挖掘过程中被删除掉的关联规则加以回收利用，从而可以获得更多的关联规则。
The traditional association rule is an expression as a Bwhich reflects the relation among positive items. But which can't reflect the negative association hidden in data.
传统的关联规则是形如a B反映正项目之间关联关系的蕴涵式，它无法反映出数据之间隐藏的负关联关系。
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。
It presents a new model for network fault management based on data fusion and data mining by defining and discussing the association rule and the frequent episodes.
并通过定义与深入分析故障告警中的关联规则和情节规则，提出了一个基于数据融合和数据挖掘技术的网络故障管理的架构模型。
This paper introduces partition method in data cube with different confidence, expatiates on multidimensional association rule data mining algorithm based on data cube partition.
介绍了在数据立方体上对于不同可信度的数据进行分块的方法，阐述了基于数据立方体分块的多维关联规则挖掘的算法。
Firstly, the method of how to guess the missing data is in detail discussed and the definition as well as the mining method of distance based association rule is given.
首先具体讨论了如何猜测丢失的数据，给出了基于距离的关联规则的定义及挖掘方法。
It is a hotspot that the data mining of time serial model, classify rule, association rule in the data mining study currently.
时间序列模式、分类规则和关联规则挖掘是当前数据挖掘研究中一个热点。
Dynamic methods employ the rule of movement of real target to erase ghosts. An applying of joint probability data association (JPDA) is presented.
动态方法利用真实目标的运动规律去除虚假目标，本文介绍了联合概率数据关联(JPDA)在此的应用。
Abstract : When mining fault information using association rule, consecutive data need to be discretized and regionalized.
摘要 ： 在利用关联规则进行故障信息挖掘时，需要将连续型数据离散化和区间化。
With the application of association rule mining method to libraries' book circulation data of some certain patrons, the concealed relations among the data could be uncovered.
对某一读者群在一定时期内所借阅图书的流通数据应用关联规则的挖掘分析方法，可以发现读者在进行专业学习时隐含的各学科知识之间的关联。
Association rule mining is the application of associated analysis in data mining, which is a very important subject with high theoretical value and extensive application.
关联规则挖掘是数据挖掘中关联分析的运用，是数据挖掘一个非常重要的学科，具有很高的理论价值和广泛的应用前景。
The minning of association rule is a important embranchment of data minning. It can open out special connection of many attribute of affairs.
关联规则挖掘是数据挖掘的一个重要分支，它用于揭示事务中各种属性之间特殊关系。
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。
Absrtact: Mining association rule is one of the most important topics of data mining.
摘 要：关联规则挖掘研究是数据挖掘研究的一项重要的内容。
Absrtact: Mining association rule is one of the most important topics of data mining.
摘 要：关联规则挖掘研究是数据挖掘研究的一项重要的内容。
应用推荐