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。
As an effective means to analyze timed data sequential pattern mining can extract episode rules from alarms, which is helpful to analyze correlation.
序列模式挖掘作为一种时序数据分析的有效手段，能够自动从告警中提取出有助于关联分析的情景规则。
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。
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。
Absrtact: association rules mining is an important branch of research on data mining, its purpose is to find the association or correlation among items.
摘要：关联模式挖掘研究是数据挖掘研究领域的重要分支之一，旨在发现模式之间存在的关联或相关关系。
Discovering association rules is one of the most important tasks of data mining, that is, to find interesting associations or correlation relationships among a large set of data items.
数据挖掘的一个重要的任务就是发现数据库中的关联规则，也就是发现数据库中项集之间有价值的规则或联系。
Association rules can find some correlation info between these fields. By use of statistic techniques of data mining we can draw exact and plain statistics reporting from the chaotic and massive data.
关联规则能发现数据中的属性字段之间的相关性，利用数据挖掘中的统计技术我们可以从纷繁杂乱的海量数据中得出条理清晰的统计数据报表。
Association rules can find some correlation info between these fields. By use of statistic techniques of data mining we can draw exact and plain statistics reporting from the chaotic and massive data.
关联规则能发现数据中的属性字段之间的相关性，利用数据挖掘中的统计技术我们可以从纷繁杂乱的海量数据中得出条理清晰的统计数据报表。
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