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Scalable knowledge discovery in point-to-multipoint environments

Authors
Cho, Sungrae
Issue Date
May-2003
Publisher
SPRINGER-VERLAG BERLIN
Citation
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2003, PT 1, PROCEEDINGS, v.2667, pp 437 - 445
Pages
9
Journal Title
COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2003, PT 1, PROCEEDINGS
Volume
2667
Start Page
437
End Page
445
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/43820
DOI
10.1007/3-540-44839-X_47
ISSN
0302-9743
1611-3349
Abstract
In this paper, a scalable knowledge discovery (SKD) algorithm is proposed for point-to-multipoint environments. An analytical model is provided for the feedback suppression performance in the SKD scheme. This model is validated with simulation results. Numerical examples show that the feedbacks can be effectively suppressed by introducing SKD algorithm.
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Cho, Sung Rae
소프트웨어대학 (소프트웨어학부)
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