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Decision Support via Text Mining

In: Handbook on Decision Support Systems 1

Author

Listed:
  • Josh Froelich

    (Megaputer Intelligence)

  • Sergei Ananyan

    (Megaputer Intelligence)

Abstract

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.

Suggested Citation

  • Josh Froelich & Sergei Ananyan, 2008. "Decision Support via Text Mining," International Handbooks on Information Systems, in: Handbook on Decision Support Systems 1, chapter 28, pages 609-635, Springer.
    • Handle: RePEc:spr:ihichp:978-3-540-48713-5_28
    DOI: 10.1007/978-3-540-48713-5_28
    as

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