Distributed data mining: a survey

Li Zeng, Ling Li, Lian Duan, Kevin Lu, Zhongzhi Shi, Maoguang Wang, Wenjuan Wu, Ping Luo

Abstract: Most data mining approaches assume that the data can be provided from a single source. If data was produced from many physically distributed locations like Wal-Mart, these methods require a data center which gathers data from distributed locations. Sometimes, transmitting large amounts of data to a data center is expensive and even impractical. Therefore, distributed and parallel data mining algorithms were developed to solve this problem. In this paper, we survey the-state-of-the-art algorithms and applications in distributed data mining and discuss the future research opportunities.