Actions for SAS text analytics for business applications : concept rules for information extraction models

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SAS text analytics for business applications : concept rules for information extraction models / Teresa Jade, Biljana Belamaric Wilsey, Michael Wallis

Author
Jade, Teresa
Published
Cary, NC : SAS Institute, [2019]
Copyright Date
©2019
Physical Description
1 online resource (1 volume) : illustrations
Additional Creators
Wilsey, Biljana Belamaric, Wallis, Michael, and SAS Institute
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Contents
Fundamentals of information extraction with SAS -- Fundamentals of named entities -- SAS predefined concepts : Enamex -- SAS predefined concepts: Timex, Numex, and Noun Group -- Fundamentals of creating custom concepts -- Concept rule types -- CONCEPT_RULE type -- Fact rule types -- Filter rule types -- REGEX rule type -- Best practices for custom concepts -- Fundamentals of data considerations -- Fundamentals of project design -- Fundamentals of model measurement.
Summary
Extract actionable insights from text and unstructured data. Information extraction is the task of automatically extracting structured information from unstructured or semi-structured text. SAS® Text Analytics for Business Applications: Concept Rules for Information Extraction Models focuses on this key element of natural language processing (NLP) and provides real-world guidance on the effective application of text analytics. Using scenarios and data based on business cases across many different domains and industries, the book includes many helpful tips and best practices from SAS text analy.
Subject(s)
ISBN
9781635266610
1635266610
1635266637 (electronic bk.)
9781635266634 (electronic bk.)
9781635266641
Bibliography Note
Includes bibliographical references.
View MARC record | catkey: 37449626