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IDA
2011
Springer
11 years 6 months ago
A parallel, distributed algorithm for relational frequent pattern discovery from very large data sets
The amount of data produced by ubiquitous computing applications is quickly growing, due to the pervasive presence of small devices endowed with sensing, computing and communicatio...
Annalisa Appice, Michelangelo Ceci, Antonio Turi, ...
SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
12 years 4 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in ļ¬nding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
AUSAI
2003
Springer
12 years 4 months ago
Efficiently Mining Frequent Patterns from Dense Datasets Using a Cluster of Computers
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Yudho Giri Sucahyo, Raj P. Gopalan, Amit Rudra
LWA
2004
12 years 29 days ago
Efficient Frequent Pattern Mining in Relational Databases
Data mining on large relational databases has gained popularity and its significance is well recognized. However, the performance of SQL based data mining is known to fall behind ...
Xuequn Shang, Kai-Uwe Sattler, Ingolf Geist
IPPS
2008
IEEE
12 years 6 months ago
Parallel mining of closed quasi-cliques
Graph structure can model the relationships among a set of objects. Mining quasi-clique patterns from large dense graph data makes sense with respect to both statistic and applica...
Yuzhou Zhang, Jianyong Wang, Zhiping Zeng, Lizhu Z...
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