SAS Text Analytics for Business Applications

Concept Rules for Information Extraction Models

Nonfiction, Computers, Application Software, Business Software, General Computing
Cover of the book SAS Text Analytics for Business Applications by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis, SAS Institute
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis ISBN: 9781635266610
Publisher: SAS Institute Publication: March 26, 2019
Imprint: SAS Institute Language: English
Author: Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
ISBN: 9781635266610
Publisher: SAS Institute
Publication: March 26, 2019
Imprint: SAS Institute
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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 books from SAS Institute

Cover of the book Multiple Imputation of Missing Data Using SAS by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book Decision Trees for Analytics Using SAS Enterprise Miner by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book Applied Data Mining for Forecasting Using SAS by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book SAS Certified Specialist Prep Guide by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book Market Data Analysis Using JMP by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book Mastering the SAS DS2 Procedure by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book Analysis of Observational Health Care Data Using SAS by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book SAS for Forecasting Time Series, Third Edition by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book Survival Analysis Using SAS by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book Simulating Data with SAS by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book Practical and Efficient SAS Programming by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book Multiple Time Series Modeling Using the SAS VARMAX Procedure by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book Biostatistics by Example Using SAS Studio by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
Cover of the book Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition by Teresa Jade, Biljana Belamaric-Wilsey, Michael Wallis
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy