期刊名称：The Online Journal of Applied Knowledge Management
印刷版ISSN：2325-4688
出版年度：2017
卷号：5
期号：2
页码：45-60
出版社：The International Institute for Applied Knowledge Management
摘要：Text analysis is a useful tool to determine what a company and its customers want in order toimprove processes and methodologies of analysis. Searches in databases may have a time seriescomponent that determines the importance and sequences of multivariate searches and itsstructure. This paper presents a methodology to simplify and model multivariate searches in timeusing the Canonical Correlation approach. The techniques shown provide a robust methodologyto simplify the analysis and create predictive models taking into account temporal dependencies.
关键词：Text analysis; Google correlate; multivariate time series; cross correlation; canonical;correlation; Radic matrices and determinant; predictive modelling.
