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T-Trees, Vertical Partitioning and Distributed Association Rule Mining
Melbourne, Florida November 19-November 22
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDM.2003.1250965Third IEEE International Conference o ...
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Frans Coenen, Paul Leng, Shakil Ahmed, "T-Trees, Vertical Partitioning and Distributed Association Rule Mining," Data Mining, IEEE International Conference on, pp. 513, Third IEEE International Conference on Data Mining (ICDM'03), 2003.
 
 
BibTex
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@article{ 10.1109/ICDM.2003.1250965,
author = {Frans Coenen and Paul Leng and Shakil Ahmed},
title = {T-Trees, Vertical Partitioning and Distributed Association Rule Mining},
journal ={Data Mining, IEEE International Conference on},
volume = {0},
year = {2003},
isbn = {0-7695-1978-4},
pages = {513},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2003.1250965},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Data Mining, IEEE International Conference on
TI - T-Trees, Vertical Partitioning and Distributed Association Rule Mining
SN - 0-7695-1978-4
SP
EP
A1 - Frans Coenen,
A1 - Paul Leng,
A1 - Shakil Ahmed,
PY - 2003
KW - null
VL - 0
JA - Data Mining, IEEE International Conference on
ER -
 
Frans Coenen, The University of Liverpool, UK
Paul Leng, The University of Liverpool, UK
Shakil Ahmed, The University of Liverpool, UK
In this paper we consider a technique (DATA-VP) for distributed (and parallel) Association Rule Mining that makes use of a vertical partitioning technique to distribute the input data amongst processors. The proposed vertical partitioning is facilitated by a novel compressed set enumeration tree data structure (the T-tree), and an associated mining algorithm (Apriori-T), that allows for computationally effective distributed/parallel ARM when compared with existing approaches.
Citation:
Frans Coenen, Paul Leng, Shakil Ahmed, "T-Trees, Vertical Partitioning and Distributed Association Rule Mining," icdm, pp.513, Third IEEE International Conference on Data Mining (ICDM'03), 2003
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