Distributed data mining: A survey

Authors

Li Zeng, Institute of Computing Technology Chinese Academy of Sciences
Ling Li, Old Dominion University
Lian Duan, Institute of Computing Technology Chinese Academy of Sciences
Kevin Lu, Brunel University London
Zhongzhi Shi, Institute of Computing Technology Chinese Academy of Sciences
Maoguang Wang, Institute of Computing Technology Chinese Academy of Sciences
Wenjuan Wu, Renmin University of China
Ping Luo, Institute of Computing Technology Chinese Academy of Sciences

Document Type

Article

Publication Date

12-1-2012

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. © 2012 Springer Science+Business Media, LLC.

Identifier

84868667281 (Scopus)

Publication Title

Information Technology and Management

External Full Text Location

https://doi.org/10.1007/s10799-012-0124-y

e-ISSN

15737667

ISSN

1385951X

First Page

403

Last Page

409

Issue

4

Volume

13

Grant

1044845

Fund Ref

National Science Foundation

Recommended Citation

Zeng, Li; Li, Ling; Duan, Lian; Lu, Kevin; Shi, Zhongzhi; Wang, Maoguang; Wu, Wenjuan; and Luo, Ping, "Distributed data mining: A survey" (2012). Faculty Publications. 17998.
https://digitalcommons.njit.edu/fac_pubs/17998