多维数据流最大频集挖掘模型和算法

为了挖掘到有价值的信息,需要挖掘多维数据流上的频繁项目集,因此引入多维项目和多维项目集的概念表示多维数据流上的项目.设计了一种紧凑、压缩的数据结构MaxFP-Tree用于维护多维项目集,并在MaxFP-Tree的基础上设计了挖掘多维数据流上最大频集的增量式更新算法.实验结果表明,设计的挖掘多维数据流中最大频集的模型和算法是高效的.

New algorithm of mining frequent closed itemsets

A new algorithm based on an FC-tree （frequent closed pattern tree） and a max-FCIA （maximal frequent closed itemsets algorithm） is presented, which is used to mine the frequent closed itemsets for solving memory and time consuming problems. This algorithm maps the transaction database by using a Hash table,gets the support of all frequent itemsets through operating the Hash table and forms a lexicographic subset tree including the frequent itemsets.Efficient pruning methods are used to get the FC-tree including all the minimum frequent closed itemsets through processing the lexicographic subset tree.Finally,frequent closed itemsets are generated from minimum frequent closed itemsets.The experimental results show that the mapping transaction database is introduced in the algorithm to reduce time consumption and to improve the efficiency of the program.Furthermore,the effective pruning strategy restrains the number of candidates,which saves space.The results show that the algorithm is effective.

关联规则挖掘算法分析与比较

由于数据挖掘的数据量巨大 ,导致关联规则挖掘中产生大量的频繁项目集。在分析经典的Apriori算法和AprioriTid算法的基础上 ,对Apriori和AprioriTid算法进行了分析与比较 ,探讨了在关系数据库环境下实现关联规则挖掘的方法。

关系数据库下的关联规则挖掘

探讨在关系数据库环境下实现关联规则挖掘的方法,首先讨论数据挖掘同关系数据库的关系,然后描述实现算法对数据库结构的要求,最后讨论算法在实现中需要解决的核心问题。