Distributed data mining: a survey

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.