Study shows that this method presents more flexibility and efficiency than the approach of independent mining association rules.
研究表明，同孤立的关联规则挖掘方法相比，该方法具有较大的灵活性和更高的效率。
In this paper, we combine cluster method with mining association rules.
本文将聚类思想引入到关联规则挖掘中。
Absrtact: Presents a method of clustering based on mining association rules.
摘 要：提出了一种基于关联规则挖掘的聚类方法。
Defining interestingness and putting forward new algorithm of mining association rules including negative items.
定义兴趣度，提出挖掘含负属性项关联规则算法。
An asynchronous algorithm APM has been proposed for mining association rules on Shared memory multi processor machine.
该文提出了在共享内存多处理机上采掘关联规则的异步算法apm。
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。
This paper proposes a new algorithm for mining association rules with composite items based on the FP-growth algorithm.
文章基于FP-增长算法提出了一种新的挖掘复合项关联规则的算法。
It also discusses some techniques of data mining such as mining association rules, mining sequential patterns and data classification.
对常用于入侵检测系统中的数据挖掘技术如关联规则，序列分析，分类分析等进行了分析。
Discovering the frequent set of item sequences in a transaction database is one of the most important tasks in mining association rules.
最大频繁项目序列集的生成是影响关联规则挖掘的关键问题，传统的算法是通过对事务数据库的多次扫描实现的。
Through defining information granule with binary string, we introduce an algorithm of mining association rules based on granular computing.
通过采用二进制串表示所定义的信息粒，提出了基于粒计算的关联规则挖掘算法。
We proposed the strategy of parallel mining association rules and describe the basic algorithms and analyze the performance of these algorithms.
提出了关联规则的并行挖掘策略并且对相应的并行算法进行了性能分析。
The key idea of mining association rules for the basket data is studied and several methods to improve algorithm efficiency and rules selection are given.
对零售业销售数据关联规则挖掘算法的关键思想进行了研究，给出了各种提高算法效率的方法以及对规则选择的方法。
Attributes in the database of tumor diagnoses are usually quantitative attributes, so quantitative attribute discretization is a problem of mining association rules.
肿瘤诊断数据库中的属性常为数量型属性，因此如何将数量型属性离散化是挖掘关联规则的难点。
The association analysis method can be applied to analyzing the microarray datasets, mining association rules of genes, and then constructing gene regulatory network.
关联分析方法用于分析微阵列数据集基因间相关联系，生成关联规则，进而构建基因调控网络。
Most quantitative association rules transform mining association rules of numeric property into boolean property, and the kernel problem is to divide the numeric data into intervals.
数值型关联规则的算法大多是将多值属性关联规则挖掘问题转化为布尔型关联规则挖掘问题，而连续属性的离散化是数值型关联规则的核心问题。
The work of author mainly focuses on two aspects in the following:On one hand, an incremental updating algorithm for mining association rules based on the change of database is proposed.
本文的研究工作主要包括以下两个方面：一方面，提出了基于数据库变化的关联规则增量式更新算法。
This paper presents a new algorithm for distributed mining association rules with item constraints called DAMICFP, which is based on a new type algorithm for association rule mining, FP-growth.
在分布式环境中挖掘约束性关联规则是当前研究的热点问题之一。
According to the basic pattern of sales based on Internet and the attribute of mix marketing strategy dug out, this paper proposes a new algorithm of mining association rules based on constraints.
针对目前我国网络销售的基本模式，在已发现的组合营销策略特点的基础上，提出了一种基于约束的关联规则挖掘新算法。
Mining association rules is an important part of data mining.
关联规则的发现是整个数据挖掘课题中的重要组成部分。
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。
Mining association rules is an important part of data mining field.
关联规则是数据挖掘中的一个重要研究内容。
Mining association rules is an important topic in the data mining research.
关联规则采掘是数据采掘中重要的研究课题。
Mining association rules is one of the primary methods used in telecommunication alarm correlation analysis.
关联规则挖掘算法是通信网告警相关性分析中的重要方法。
Mining association rules can find out some potential correlations in large quantity of data and has been applied widely in some fields.
关联规则挖掘可以发现大量数据项集之间隐含的关系，在许多领域得到了广泛应用。
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。
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.
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 is an important aspect of the study of data mining, and one of the important problems is the evaluation of interestingness of the discovered rules.
关联规则挖掘是数据挖掘研究中的一个重要方面，而其中一个重要问题是对挖掘出的规则的兴趣度的评估。
This paper discusses the essential concepts, the procedure of Mining Association Rules, an active field in KDD (Knowledge Discovery in Database), as well as the open problems faced in this field.
围绕KDD的一个重要发现任务——关联规则发现，介绍了这一领域基本概念、处理技术以及面临的问题。
Mining association rules with ontological information bases on built domain ontology, using an algorithm of data mining, to produce semantic association rules which are more greatly satisfying users.
基于本体的关联规则挖掘，是利用构建好的领域本体，结合数据挖掘算法，产生出具有语义的更符合用户需求的关联规则。
Mining association rules with ontological information bases on built domain ontology, using an algorithm of data mining, to produce semantic association rules which are more greatly satisfying users.
基于本体的关联规则挖掘，是利用构建好的领域本体，结合数据挖掘算法，产生出具有语义的更符合用户需求的关联规则。
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