All sorts of advanced data-mining rules can be triggered in this way.
可以用这种方式触发各种各样的高级数据挖掘规则。
A transition matrix among activities was established based on process logs, and the mining rules of basic process logical relationships were defined.
基于日志建立转移矩阵，定义基本过程逻辑关系的挖掘规则，并据此规则设计了挖掘算法。
This method conquers the disadvantage of traditional association rules mining methods, mining rules while mining frequent-item set, so the mining efficiency is greatly enhanced.
该方法克服了传统关联规则挖掘方法的不足，在产生频繁项集的同时进行规则挖掘，从而提高了挖掘效率。
Data mining, at its core, is the transformation of large amounts of data into meaningful patterns and rules.
数据挖掘，就其核心而言，是指将大量数据转变为有实际意义的模式和规则。
Association rules are one of the techniques used in data mining, and particularly useful with e-commerce transactional information.
关联规则是在数据挖掘中所使用的一种技术，并对电子商务事务信息非常有用。
Mining association rules require two pieces of data, the transaction and what was bought in that transaction.
挖掘关联规则需要两方面的数据，事务及该事务中所包含的信息。
You have learned that data mining with association rules is a useful way to identify related items in your customers' shopping carts.
您已经学习到了使用关联规则的数据挖掘是识别出在顾客购物车中的相关条目的有用的方式。
Ramesh has said that all applications for mining in forest areas now requires not only the forestry clearances, but also evidence that the rules of the Tribal Rights Act have been followed.
拉梅什部长已经指出，森林地区的所有矿物开采申请现在不仅要获得森林部的许可证，还应证明符合部落权利法的规定。
In the following example, see how to create the mining flow, creating the association model and extracting the rules from it.
下面的示例显示了如何创建挖掘流程，同时创建关联模型并从中提取规则。
However, looking back to the top of the article, data mining isn't just about outputting a single number: It's about identifying patterns and rules.
不过，回过头来看看本文的开头部分，我们知道数据挖掘绝不是仅仅是为了输出一个数值：它关乎的是识别模式和规则。
More importantly, I talked about three techniques used in data mining that can turn your confusing and useless data into meaningful rules and trends.
而且更重要的是，在这两个部分中我谈及了数据挖掘中常用的三种技术，它们可以将难以理解的无用数据转变为有意义的规则和趋势。
Within the report, you can enter parameters to change the mining parameters. In this example, a revenue-per-product list allows you to drill-through to association rules for the specific products.
在本示例中，有一个针对每个产品的收入列表，借助它就能够穿透钻取特定产品的关联规则。
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
InfoSphere Warehouse design Studio is the Eclipse-based tooling platform used to design workload rules, data transformation flows, and analytical flows for data mining and text analytics.
InfoSphere WarehouseDesignStudio是基于Eclipse的工具平台，用于为数据挖掘和文本分析设计工作负载规则、数据转换流和分析流。
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。
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。
Article 9 the following items in mining designs must comply with the safety rules and technological standards for mining industry.
第九条矿山设计下列项目必须符合矿山安全规程和行业技术规范。
The campaign is now trying to get mining companies to sign up to these rules, and jewellers to eschew gold that has come from unacceptable sources.
现在，该运动正致力于使矿产公司签字接受这些准则，并使珠宝商拒绝那些来历不明的黄金。
Data mining strives to turn a lot of misinformation (in the form of scattered data) into useful information by creating models and rules.
数据挖掘就是通过创建模型和规则来将大量的不可用信息(通常是分散的数据形式)变成有用的信息。
The single minimum support degree is used in the existing association rules mining methods mostly.
现有的关联规则挖掘方法中，大多采用单一的最小支持度。
The third is finding the information of products use and special rules by using the sequence pattern mining in the Data mining technique.
其三是使用数据挖掘技术中的序列模式挖掘技术获得产品使用情况和特殊规律的信息。
Mining association rules is a major aspect of data mining research.
挖掘关联规则是数据挖掘研究的一个重要方面。
Based on data-distort method, we propose privacy preserving association rules mining algorithm IFB-PPARM using efficient data structure namely inverted file.
基于数据变换法，提出使用高效数据结构即倒排文件的隐私保护关联规则挖掘算法ifb - PPARM。
Mining association rules is a major aspect of data mining research, and maintaining discovered association rules is of equal importance.
挖掘关联规则是数据挖掘研究的一个重要方面，而维护已发现的关联规则同样是重要的。
The conventional framework for mining association rules is the support-confidence framework which has some limitations.
传统的关联规则数据挖掘的支持度-置信度框架存在着弊端。
Mining quantitative association rules is an important task of data mining.
量化关联规则的挖掘是数据挖掘的一项重要任务。
Mining quantitative association rules is an important task of data mining.
量化关联规则的挖掘是数据挖掘的一项重要任务。
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