DocumentCode
2370275
Title
T-trees, vertical partitioning and distributed association rule mining
Author
Coenen, Frans ; Leng, Paul ; Ahmed, Shakil
Author_Institution
Dept. of Comput. Sci., Liverpool Univ., UK
fYear
2003
fDate
19-22 Nov. 2003
Firstpage
513
Lastpage
516
Abstract
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.
Keywords
data mining; distributed processing; tree data structures; DATA-VP technique; distributed Apriori-T algorithm vertical partitioning; distributed association rule mining; parallel association rule mining; tree data structure; Association rules; Computational efficiency; Computer science; Concurrent computing; Data mining; Distributed computing; Indexing; Itemsets; Partitioning algorithms; Tree data structures;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, 2003. ICDM 2003. Third IEEE International Conference on
Print_ISBN
0-7695-1978-4
Type
conf
DOI
10.1109/ICDM.2003.1250965
Filename
1250965
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