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» An Empirical Study on Web Mining of Parallel Data
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MASCOTS
2004
14 years 11 months ago
The N-Burst/G/1 Model with Heavy-Tailed Service-Times Distribution
This study introduces a new analytic queuing model, the N-Burst/G/1 model with heavy-tailed service-time distribution, which captures many of the issues that affect Web servers as...
Ronit Nossenson, Hagit Attiya
KDD
1999
ACM
199views Data Mining» more  KDD 1999»
15 years 2 months ago
The Application of AdaBoost for Distributed, Scalable and On-Line Learning
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang
JIIS
2008
133views more  JIIS 2008»
14 years 9 months ago
Maintaining frequent closed itemsets over a sliding window
In this paper, we study the incremental update of Frequent Closed Itemsets (FCIs) over a sliding window in a high-speed data stream. We propose the notion of semi-FCIs, which is to...
James Cheng, Yiping Ke, Wilfred Ng
ISPASS
2009
IEEE
15 years 4 months ago
Lonestar: A suite of parallel irregular programs
Until recently, parallel programming has largely focused on the exploitation of data-parallelism in dense matrix programs. However, many important application domains, including m...
Milind Kulkarni, Martin Burtscher, Calin Cascaval,...
IEEEHPCS
2010
14 years 8 months ago
Discovering closed frequent itemsets on multicore: Parallelizing computations and optimizing memory accesses
The problem of closed frequent itemset discovery is a fundamental problem of data mining, having applications in numerous domains. It is thus very important to have efficient par...
Benjamin Négrevergne, Alexandre Termier, Je...