Abstract
Distributed Data Mining (DDM) is the process of mining distributed and heterogeneous datasets. DDM is widely seen as a means of addressing the scalability issue of mining large data sets. Consequently, there is an emerging focus on optimisation of the DDM process. In this paper we present cost formulae for estimating the communication and computation time for different distributed data mining scenarios. © 2002 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Krishnaswamy, S., Zaslavsky, A., & Loke, S. W. (2002). Techniques for estimating the computation and communication costs of Distributed Data Mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2329 LNCS, pp. 603–612). Springer Verlag. https://doi.org/10.1007/3-540-46043-8_61
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