Context: Data Mining (DM) method has been evolving year by year and as of today there is also the enhancement of DM technique that can be run several times faster than the traditional one, called Distributed Data Mining (DDM). It is not a new field in data processing actually, but in the recent years many researchers have been paying more attention on this area. Problems: The number of publication regarding DDM in high reputation journals and conferences has increased significantly. It makes difficult for researchers to gain a comprehensive view of DDM that require further research. Solution: We conducted a systematic literature review to map the previous research in DDM field. Our objective is to provide the motivation for new research by identifying the gap in DDM field as well as the hot area itself. Result: Our analysis came up with some conclusions by answering 7 research questions proposed in this literature review. In addition, the taxonomy of DDM research area is presented in this paper. Finally, this systematic literature review provides the statistic of development of DDM since 2000 to 2015, in which this will help the future researchers to have a comprehensive overview of current situation of DDM.

中文翻译：

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分布式数据挖掘研究的调查和分类：系统文献综述

背景：数据挖掘 (DM) 方法逐年发展，截至今天，DM 技术也得到了增强，其运行速度比传统技术快数倍，称为分布式数据挖掘 (DDM)。这实际上并不是数据处理的一个新领域，但近年来许多研究人员对这一领域给予了更多的关注。问题：DDM在高声誉期刊和会议上的发表数量显着增加。研究人员很难全面了解需要进一步研究的 DDM。解决方案：我们进行了系统的文献回顾，以绘制 DDM 领域的先前研究。我们的目标是通过确定 DDM 领域的差距以及热点领域本身，为新研究提供动力。结果：我们的分析通过回答本文献综述中提出的 7 个研究问题得出了一些结论。此外，本文还介绍了 DDM 研究领域的分类。最后，本系统的文献综述提供了 2000 年至 2015 年 DDM 发展的统计数据，这将有助于未来的研究人员全面了解 DDM 的现状。