多关系频繁项集的并行获取

Paralleled Acquisition of Multi-Relational Frequent Itemsets

现有的多关系频繁项集的挖掘都是在单机系统环境下进行的,存在着一定的效率问题.由此提出了一种并行处理多个表之间关系的算法,将表进行两两合并,在每台单机上只需要处理两张表的结果,提高了挖掘效率,减少了挖掘时间.

Now, most multi-relational frequent itemsets are found in a PC, following some efficient problems. In this paper, we proposed a method by which we can process data between many tables in relational database parallel. We only need deal with the result of the two tables in one PC by merging two tables, and we can enhance the efficiency and reduce the time in the process of the data mining.