Text as data: computational methods of understanding written expression using SAS

Text mining and text analytics -- Text analytics process overview -- Text data source capture -- Document content and characterization -- Textual abstraction : latent structure, dimension reduction -- Classification and prediction -- Boolean methods of classification and prediction -- Speech to text.

"This book provides a high-level, integrated overview of text analytics and the role of SAS software in the ever-evolving information technology environment. The author uses his 18 years of experience to show the reader how using multiple sources of data and machine learning approaches can produce superior results. He emphasizes text as qualitative data in the context of traditional quantitative data analytics. The book begins with a description of the structure and dynamics of the text analytics process, before delving deeper into his combined linguistic + quantitative approach to analyzing data. Topics covered include numeric vs. textual data, expression parsing and detection, and text maps"--