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Clustering high dimensional data streams based on N-most interesting itemsets mining.

, , , , and . FSKD, page 412-416. IEEE, (2013)

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An Efficient Strip-Mining Algorithm for Improving SRF Bandwidth Utilization on Imagine., , , and . SITIS, page 453-460. IEEE Computer Society, (2007)A Novel Pruning Technique for Mining Maximal Frequent Itemsets., , , and . FSKD (3), page 469-473. IEEE Computer Society, (2007)0-7695-2874-0.Scientific Computing Applications on the Imagine Stream Processor., , , and . Asia-Pacific Computer Systems Architecture Conference, volume 4186 of Lecture Notes in Computer Science, page 38-51. Springer, (2006)Parallel verilog simulation: architecture and circuit partition., , , , and . ASP-DAC, page 644-646. IEEE Computer Society, (2004)MV-FT: Efficient Implementation for Matrix-Vector Multiplication on FT64 Stream Processor., , and . ICDS, page 134-139. IEEE Computer Society, (2008)Model-guided strip size selection for minimal execution time on imagine stream processor., , , , and . CIT, page 267-272. IEEE Computer Society, (2008)Concurrency Analysis and Implementation of SAR Imaging Algorithm Oriented to Hybrid Storage System., , , and . CyberC, page 314-319. IEEE Computer Society, (2015)Cluster performance oriented characteristics of network simulations., , , , and . FSKD, page 653-657. IEEE, (2013)Clustering high dimensional data streams based on N-most interesting itemsets mining., , , , and . FSKD, page 412-416. IEEE, (2013)OSS: Efficient Compiler Approach for Selecting Optimal Strip Size on the Imagine Stream Processor., , , and . AINA Workshops, page 337-342. IEEE Computer Society, (2008)