Accelerating discovery mining unstructured information for hypothesis generation

Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation describes a novel approach to scientific research that uses unstructured data analysis as a generative tool for new hypotheses

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Bibliographic Details
Main Author: Spangler, Scott (Author)
Format: Book
Language:English
Published: Boca Raton, FL CRC Press 2016
Series:Chapman & Hall/CRC data mining and knowledge discovery series 37
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504 |a Includes bibliographical references and index 
505 0 |a Introduction -- Why Accelerate Discovery? -- Form and Function -- Exploring Content to Find Entities -- Organization -- Relationships -- Inference -- Taxonomies -- Orthogonal Comparison -- Visualizing the Data Plane -- Networks -- Examples and Problems -- Problem: Discovery of Novel Properties of Known Entities -- Problem: Finding New Treatments for Orphan Diseases from Exisiting Drugs 
520 |a Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation describes a novel approach to scientific research that uses unstructured data analysis as a generative tool for new hypotheses 
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