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

Text data management and analysis : a practical introduction to information retrieval and text mining / First Edition (2회 대출)

자료유형
단행본
개인저자
Zhai, ChengXiang. Massung, Sean.
서명 / 저자사항
Text data management and analysis : a practical introduction to information retrieval and text mining / ChengXiang Zhai, University of Illinois at Urbana-Champaign, Sean Massung, University of Illinois at Urbana-Champaign.
판사항
First Edition.
발행사항
[New York] :   ACM Books,   c2016.  
형태사항
xx, 510 p. : ill. (some col.) ; 24 cm.
총서사항
ACM Books,2374-6769 ; #12
ISBN
9781970001198 9781970001167 (pbk.)
요약
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.
서지주기
Includes bibliographical references (p. 477-488) and index.
일반주제명
Natural language processing (Computer science). Data mining. Computational linguistics --Statistical methods.
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100 1 ▼a Zhai, ChengXiang.
245 1 0 ▼a Text data management and analysis : ▼b a practical introduction to information retrieval and text mining / ▼c ChengXiang Zhai, University of Illinois at Urbana-Champaign, Sean Massung, University of Illinois at Urbana-Champaign.
250 ▼a First Edition.
260 ▼a [New York] : ▼b ACM Books, ▼c c2016.
300 ▼a xx, 510 p. : ▼b ill. (some col.) ; ▼c 24 cm.
490 1 ▼a ACM Books, ▼x 2374-6769 ; ▼v #12
504 ▼a Includes bibliographical references (p. 477-488) and index.
520 ▼a 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.
650 0 ▼a Natural language processing (Computer science).
650 0 ▼a Data mining.
650 0 ▼a Computational linguistics ▼x Statistical methods.
700 1 ▼a Massung, Sean.
830 0 ▼a ACM books ; ▼v #12.
945 ▼a KLPA

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