Abstract
Text analysis is a useful tool to determine what a company and its customers want in order to improve processes and methodologies of analysis. Searches in databases may have a time series component that determines the importance and sequences of multivariate searches and its structure. This paper presents a methodology to simplify and model multivariate searches in time using the Canonical Correlation approach. The techniques shown provide a robust methodology to simplify the analysis and create predictive models taking into account temporal dependencies.
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