The growing volume of textual data presents genuine, modern day challenges that traditional decision support systems, focused on quantitative data processing, are unable to address. The costs of competitive intelligence, customer experience metrics, and manufacturing controls are escalating as organizations are buried in piles of open-ended responses, news articles and documents. The emerging field of text mining is capable of transforming natural language into actionable results, acquiring new insight and managing information overload.
CITATION STYLE
Froelich, J., & Ananyan, S. (2008). Decision Support via Text Mining. In Handbook on Decision Support Systems 1 (pp. 609–635). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-48713-5_28
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