Titlebook: Scientific and Statistical Database Management; 24th International C Anastasia Ailamaki,Shawn Bowers Conference proceedings 2012 Springer-V

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Probabilistic Frequent Pattern Growth for Itemset Mining in Uncertain Databasesertain) transaction databases. Uncertain transaction databases consist of sets of existentially uncertain items. The uncertainty of items in transactions makes traditional techniques inapplicable. In this paper, we tackle the problem of finding probabilistic frequent itemsets based on possible world

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Efficient Range Queries over Uncertain Strings the presence of uncertainty, however, answering range queries is more challenging than those in deterministic scenarios since there are exponentially many possible worlds to be considered. This work extends existing filtering techniques tailored for deterministic strings to uncertain settings. We f

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CUMB

Partitioning and Multi-core Parallelization of Multi-equation Forecast Modelsons. The employed statistical models already provide very accurate predictions, but recent developments in these domains pose new requirements on the calculation speed of the forecast models. Especially, the often used multi-equation models tend to be very complex and their estimation is very time c

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Integrating GPU-Accelerated Sequence Alignment and SNP Detection for Genome Resequencing Analysisnalysis workflow is to first perform sequence alignment and then detect SNPs among the aligned sequences. In practice, the performance bottleneck in this workflow is usually the intermediate result I/O due to the separation of the two components, especially when the in-memory computation has been ac