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- Title
Multivariate text mining for process improvement using cross-canonical correlation analysis.
- Authors
Guerrero Cusumano, Jose Luis
- 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.
- Subjects
TEXT mining; CANONICAL correlation (Statistics); TIME series analysis
- Publication
Online Journal of Applied Knowledge Management, 2017, Vol 5, Issue 2, p45
- ISSN
2325-4688
- Publication type
Article
- DOI
10.36965/ojakm.2017.5(2)45-60