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» An Empirical Study on Web Mining of Parallel Data
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MASCOTS
2004
15 years 1 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 4 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 12 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 6 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 10 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...