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。
Association rules are one of the techniques used in data mining, and particularly useful with e-commerce transactional information.
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。
You have learned that data mining with association rules is a useful way to identify related items in your customers' shopping carts.
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。
Mining association rules require two pieces of data, the transaction and what was bought in that transaction.
数据挖掘通常涉及到一些标准的任务，包括聚集、分类、回归分析和关联性规则学习。
Data mining commonly involves a few standard tasks that include clustering, classification, regression, and associated rule learning.
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
To create the association rule mining model and extract the rules to a database table, do the following
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。
The conventional framework for mining association rules is the support-confidence framework which has some limitations.
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。
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.
将关联规则挖掘引入医学资料的分析之中，弥补传统统计学方法的不足，最大可能地获取数据中含有的信息是本研究的目的。
Introducing association rules into the analysis of medical data, making up statistics methods, and getting rich information possibly are the main aim of the study.
数据挖掘是当今国际人工智能和数据库研究的新兴领域，而关联规则的更新是数据挖掘的一个重要研究内容。
Data mining is a new emerging area for the research of artificial intelligence and databases, in which incremental updating of association rules is an important research topic.
挖掘关联规则是数据挖掘研究的一个重要方面。
Mining association rules is a major aspect of data mining research.
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。
Based on data-distort method, we propose privacy preserving association rules mining algorithm IFB-PPARM using efficient data structure namely inverted file.
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。
Mining association rules is a major aspect of data mining research, and maintaining discovered association rules is of equal importance.
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.
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 is a method of data mining, whose typical application is the analysis of shopping basket in supermarket.
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。
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.
本文的内容包括两个方面：关联规则挖掘算法研究和数据挖掘应用系统体系结构的研究。
The content of this paper includes two respects: research of data mining algorithms and the system structure of the application platform of data mining.
介绍了遥感图像数据的关联规则挖掘方法。
This paper describes the methods of data mining by means of association rules.
讨论了区间值关系数据库上模糊关联规则的挖掘算法与预测方法。
Mining algorithm and prediction method of fuzzy association rules are discussed in this paper.
通过实验验证，在关联规则数据挖掘中采用二进制序列集这一组织数据方法是有效且可行的。
And making an experiment on it, it proves that binary system sequences set is efficient and feasible as an approach of organization data based on mining of association rules.
挖掘肿瘤诊断数据库中的关联规则，能为肿瘤诊断提供有用的信息。
Association rules used in mining the database of tumor diagnoses can provide useful information for tumor diagnoses.
其中规则库中包含正常行为规则和异常行为规则，使得原型系统在理论上既可实现误用检测也可实现异常检测，并采用关联规则挖掘模块对网络连接数据进行处理。
The rule sets of the system include normal behavior rules and abnormal behavior rules, it make the system can carry out the anomaly detection and misuse detection in theory.
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。
Association rule mining which is a method of data mining reveals the latent information and knowledge.
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。
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.
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。
Several major kinds of data mining methods, including characterization, classification, association rule, clustering, outlier detection, pattern matching, data visualization, and so on.
数据库中关联规则挖掘一直是人们研究的热点，而模糊集理论的应用又为这一领域注入了新的活力。
Mining association rules in databases is the hot point in people's researches and the application of fuzzy-set theory has added new energy into the field.
空间关联规则是空间数据中重要的隐含信息，本文采用数据挖掘的方法研究空间关联规则信息的提取。
Spatial Association Rules is important information of implying in the data, this paper adopts method research Spatial Association Rules abstraction of message that data excavate.
空间关联规则是空间数据中重要的隐含信息，本文采用数据挖掘的方法研究空间关联规则信息的提取。
Spatial Association Rules is important information of implying in the data, this paper adopts method research Spatial Association Rules abstraction of message that data excavate.
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