SAS Text Analytics for Business Applications /

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...

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Bibliographic Details
Main Authors: Jade, Teresa (Author), Belamaric-Wilsey, Biljana (Author), Wallis, Michael (Author)
Corporate Author: Safari, an O'Reilly Media Company
Format: eBook
Language:English
Published: SAS Institute, 2019.
Edition:1st edition.
Subjects:
Online Access:Connect to this electronic resource
Description
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 analytics experts to ensure fast, valuable insight from your textual data. Written for a broad audience of beginning, intermediate, and advanced users of SAS text analytics products, including SAS Visual Text Analytics, SAS Contextual Analysis, and SAS Enterprise Content Categorization, this book provides a solid technical reference. You will learn the SAS information extraction toolkit, broaden your knowledge of rule-based methods, and answer new business questions. As your practical experience grows, this book will serve as a reference to deepen your expertise.
Item Description:Electronic resource.
Physical Description:1 online resource (308 pages)
Format:Mode of access: World Wide Web.