Infobright for analyzing social sciences data
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There are considerable challenges in analyzing, interpreting, and reporting word-based social sciences data. Infobright data warehousing technology was used to analyze a typical data set from the social sciences. Infobright was found to require augmentation for analyzing qualitative data provided as short stories by human subjects. A requirements specification for mining data that are subject to interpretation is proposed and left to the Infobright designers to implement should they so choose. Infobright was chosen as a system for implementing the data set because its rough set based intelligence appears to be extensible with moderate effort to implement the data warehousing requirements of word based data. © 2009 Springer-Verlag Berlin Heidelberg.
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