So, distributed and parallel data mining pattern is one of hot problems of research currently.
因此，分布式并行数据挖掘处理模式是目前研究的热点问题之一。
A parallel data mining architecture is put forward, facing to business intelligence and having higher data mining efficiency.
提出了一个面向商业智能的、具有较高数据挖掘效率的并行数据挖掘体系结构。
There were problems in traditional parallel algorithms for mining frequent itemsets more or less: data deviation, large scale communication, frequent synchronization and scanning database.
传统的挖掘频繁项集的并行算法存在数据偏移、通信量大、同步次数较多和扫描数据库次数较多等问题。
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