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。
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。
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。
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。
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