
SAS Text Analytics for Business Applications
Concept Rules for Information Extraction Models
SAS Institute (Publisher)
Published on 26. March 2019
Book
Paperback/Softback
308 pages
978-1-63526-664-1 (ISBN)
Description
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.
More details
Language
English
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 17 mm
Weight
579 gr
ISBN-13
978-1-63526-664-1 (9781635266641)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Teresa Jade | Biljana Belamaric-Wilsey | Michael Wallis
SAS Text Analytics for Business Applications
Concept Rules for Information Extraction Models
E-Book
03/2019
SAS Institute
€66.49
Available for download