The data mining of association rules is an essential research aspect in the data mining fields.
关联规则挖掘是数据挖掘领域的重要研究方向。
Absrtact: mining of association rules is an important research topic among the various data mining problems.
摘要：关联规则挖掘是数据挖掘领域中的重要研究内容之一。
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.
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。
The stress of main memory is abated, the times of scan of database are cut down, and the algorithm executes more efficient mining of association rules in time-variant database.
该算法通过分组及时舍弃挖掘过程中生成的非频繁项目集，有效降低主存压力，减少对数据库的扫描次数，能够对时变数据库进行高效地关联规则挖掘。
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。
The output of association mining is a set of rules of the form.
关联挖掘的输出是一组采用以下形式的规则。
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 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 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 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。
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.
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。
Association rules used in mining the database of tumor diagnoses can provide useful information for tumor diagnoses.
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。
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。
Association rules is an important method of data mining techniques.
关联规则是一种重要的数据挖掘技术。
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。
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。
Secondly, we study the problem of mining valid and non-Redundant association rules.
第二是研究了挖掘有效且无冗余关联规则的问题。
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。
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。
Two methods of mining normal association rules are compared in the last part.
最后对两种挖掘正态关联规则的方法进行了比较。
Mining algorithm and prediction method of fuzzy association rules are discussed in this paper.
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。
The algorithm of mining inter-transactional quantitative association rules is propose.
提出了事务间量化关联规则的挖掘算法。
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。
According to the analysis of association rules mining algorithms, the CPH and AOAA algorithms are presented.
根据对关联规则挖掘算法的分析，提出了CPH算法和AOAA算法。
The mining method of the linguistic value association rules is also provided.
另外，给出了语言值关联规则的挖掘方法。
The method of mining normal association rules is also provided. With this method, all interesting normal association rules can be mined.
接着给出正态关联规则的挖掘方法，此方法能挖掘出所有有意义的正态关联规则。
The mining of weighted association rules is a primary method used in alarm correlation analysis.
加权关联规则挖掘是告警相关性分析的重要手段。
The mining of weighted association rules is a primary method used in alarm correlation analysis.
加权关联规则挖掘是告警相关性分析的重要手段。
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