Text data management and analysis : a practical introduction to information retrieval and text mining /

Bibliographic Details
Main Authors: Zhai, ChengXiang (Author), Massung, Sean (Author)
Format: eBook
Language:English
Published: [New York] : [San Rafael, California] : Association for Computing Machinery ; Morgan & Claypool, 2016.
Edition:First edition.
Series:ACM books ; #12.
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Abstract:The growth of "big data" created unprecedented opportunities to leverage computational and statistical approaches to turn raw data into actionable knowledge that can support various application tasks. This is especially true for the optimization of decision making in virtually all application domains such as health and medicine, security and safety, learning and education, scientific discovery, and business intelligence. Just as a microscope enables us to see things in the "micro world" and a telescope allows us to see things far away, one can imagine a "big data scope" would enable us to extend our perception ability to "see" useful hidden information and knowledge buried in the data, which can help make predictions and improve the optimality of a chosen decision. This book covers general computational techniques for managing and analyzing large amounts of text data that can help users manage and make use of text data in all kinds of applications.
Physical Description:1 online resource PDF (xx, 510 pages) : illustrations.
Also available in print.
Format:Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Bibliography:Includes bibliographical references and index.
ISBN:9781970001174
ISSN:2374-6777 ;
DOI:10.1145/2915031
Access:Abstract freely available; full-text restricted to subscribers or individual document purchasers.