Li ZengLida XuZhongzhi ShiMaoguang WangWenjuan Wu
In information systems in particular business Intelligence systems, for data produced at physically distributed locations most traditional data mining approaches require data to be transmitted to a single location for centralized processing and mining. However, the continual transmission of a large number of data to a central location must be impractical and expensive. Thus, distributed and parallel data mining algorithms and applications were rapidly developed. The paper surveys the-state-of-the art in approaches and applications of distributed computing environment. The goal is to summarize a brief introduction to this field with pointers for further exploration.
Eugen VasilescuSami H. O. SalihR. Pérez