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The vigorous growth of big data has triggered both opportunities and challenges in business and industry. However, Web big data distributed in diverse sources with multiple data structures frequently conflict with each other, i.e. inconsistency in cross-source Web big data. In this paper, we propose a state-of-the-art architecture of auto-discovering inconsistency with Web big data. Our contributions...
The data generated by scientific simulation, sensor, monitor or optical telescope has increased with dramatic speed. In order to analyze the raw data fast and space efficiently, data pre-process operation is needed to achieve better performance in data analysis phase. Current research shows an increasing tread of adopting MapReduce framework for large scale data processing. However, the data access...
It is well known that the classical regression analysis, especially parametric regression analysis, is one of the important methods of extracting information from data sets. A family of regression functions, called fuzzy c-regression models (FCRM), has been presented which can be used to characterize the linear relationship to certain types of mixed data. More generally, an effective and robust method,...
Biclustering techniques, for simultaneous row-column clustering, are widely used in the analysis of the gene expression data. Many different biclustering techniques have been proposed, such as the iterative signature algorithm (ISA) (Bergmann et al., 2003), global biclustering (Wolf et al., 2006), evolutionary fuzzy biclustering (Mitra et al., 2007), etc. Among these techniques, the plaid model is...
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