Frequent item mining algorithms need to perform as little data stream scanning as possible while using limited size of memory.
数据流频繁项挖掘算法需要利用有限的内存，以尽量少的次数扫描数据流就能得到频繁项。
To meet more extensive mining demand, this paper presents another immune association rule mining method, which aimes at the largest frequent item set.
针对更一般的挖掘需求，提出一种以最大频繁项目集为目标的免疫挖掘算法。
Based on a new idea of frequent item table which can be directly used in fast frequent mode mining, an effective FP_growth mining algorithm is presented in this paper.
提出了一种可直接用于快速频繁模式挖掘的频繁项目表的概念，并实现了具体的频繁模式增量挖掘方法。
This method conquers the disadvantage of traditional association rules mining methods, mining rules while mining frequent-item set, so the mining efficiency is greatly enhanced.
该方法克服了传统关联规则挖掘方法的不足，在产生频繁项集的同时进行规则挖掘，从而提高了挖掘效率。
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。
The experiments show that FP-DFS has good efficiency in frequent item-set mining.
实验表明，该算法对于频繁项集挖掘具有比较高的效率。
Discovering frequent item sets is the main way of association rules mining, and it is also the focus of the study in algorithms for association rules mining.
发现频繁项集是关联规则挖掘的主要途径，也是关联规则挖掘算法研究的重点。
The results show that rules got by this method are concise and valuable. Furthermore, the generation of frequent item sets is improved remarkably, thus rapid data mining is achieved.
应用结果表明这样得到的规则简洁明确，规则具有实用价值，并且频繁集优化的效果显著，达到了快速挖掘的目的。
The results show that rules got by this method are concise and valuable. Furthermore, the generation of frequent item sets is improved remarkably, thus rapid data mining is achieved.
应用结果表明这样得到的规则简洁明确，规则具有实用价值，并且频繁集优化的效果显著，达到了快速挖掘的目的。
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