The typical Mining Association Rules algorithm is by R.
典型的关联规则发现算法是由R。
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。
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。
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。
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。
And examples of the algorithm is an effective method for mining association rules.
并用实例说明该算法是一种有效的关联规则挖掘方法。
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。
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。
We need search after the new methods of mining association rules, so as to avoid several bugs of frequent items.
为了避免频集方法的一些缺陷，我们需要探索挖掘关联规则的新方法。
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。
The problem of mining association rules with lattices is descried and the lower bonds of the problem′s are gained.
对关联规则挖掘问题建立了完全格描述并给出了问题规模下限，提出了一种基于搜索空间划分的项集频度计算模型。
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。
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。
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。
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。
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 dissertation brings about conclusions below:(1) The FDM and CD are main stream algorithms for mining association rules in distributed databases.
本文的主要工作和结论如下：（1）对于分布式关联规则挖掘问题，目前的主要算法是CD算法和FDM算法。
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。
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。
Example shows that a new resolution ratio and combination of data mining association rules theory of gray correlation assessment method is an effective method.
实例分析表明采用新的分辨系数并且结合数据挖掘的关联规则理论的灰色关联评估法是一种有效的方法。
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。
To reduce invalid rules in mining association rules, we have analyzed the reasons and presented to add the effect or the relative confidence in the judgment criteria.
为了减少关联规则挖掘中的无效关联规则，我们分析了其原因，提出了二种改进方法，即在衡量标准中增加影响度或相对置信度。
To reduce invalid rules in mining association rules, we have analyzed the reasons and presented to add the effect or the relative confidence in the judgment criteria.
为了减少关联规则挖掘中的无效关联规则，我们分析了其原因，提出了二种改进方法，即在衡量标准中增加影响度或相对置信度。
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