Efficient and Private Processing of Analytical Queries in Scientific Datasets
Large amount of data is generated by applications used in basic-science research and development applications. The size of data introduces great challenges in storage, analysis and preserving privacy. This dissertation proposes novel techniques to efficiently analyze the data and reduce storage spac...
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| Format: | Others |
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Scholar Commons
2013
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| Online Access: | http://scholarcommons.usf.edu/etd/4822 http://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=6018&context=etd |