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010 a| 2017448518;

020 a| 9781970001198;

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049 a| EREEa| NEHH;

050 00 a| QA76.9.N38b| Z43 2016;

084 a| 06.642| bcl;

100 1 a| Zhai, ChengXiang.?| UNAUTHORIZED;

245 10 a| Text data management and analysish| [electronic resource] :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| [2016];

300 a| xx, 510 pages :b| illustrations (some color) ;c| 25 cm.;

490 1 a| ACM Books,x| 2374-6769 ;v| #12;

504 a| Includes bibliographical references (pages 477-488) and index.;

506 a| Available only to authorized users.;

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.;

538 a| Mode of access: World Wide Web;

650 0 a| Natural language processing (Computer science)=| ^A235570;

650 0 a| Data mining.=| ^A408868;

650 0 a| Computational linguisticsx| Statistical methods.=| ^A92497;

650 7 a| Computational linguisticsx| Statistical methods.2| fast0| (OCoLC)fst00872003;

650 7 a| Data mining.2| fast0| (OCoLC)fst00887946;

650 7 a| Natural language processing (Computer science)2| fast0| (OCoLC)fst01034365;

650 7 a| Text Mining2| gnd;

650 7 a| Wissenserwerb2| gnd;

650 7 a| Data Mining2| gnd;

650 7 a| Wissensextraktion2| gnd;

650 7 a| Mustererkennung2| gnd;

655 0 a| Electronic books.=| ^A491897;

700 1 a| Massung, Sean.?| UNAUTHORIZED;

830 0 a| ACM booksv| #12.x| 2374-6769=| ^A1287316;

856 40 z| Full text available from Ebook Central - Academic Completeu| https://ebookcentral.proquest.com/lib/eastcarolina/detail.action?docID=6954877;

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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.

Author/creator	Zhai, ChengXiang
Other author	Massung, Sean.
Format	Electronic
Edition	First Edition.
Publication Info	[New York] : ACM Books, [2016]
Description	xx, 510 pages : illustrations (some color) ; 25 cm.
Supplemental Content	Full text available from Ebook Central - Academic Complete
Subjects	Natural language processing (Computer science) Data mining. Computational linguistics--Statistical methods.

Series	ACM Books, 2374-6769 ; #12 ACM books #12. 2374-6769 ^A1287316
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.
Bibliography note	Includes bibliographical references (pages 477-488) and index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Genre/form	Electronic books.
LCCN	2017448518
ISBN	9781970001198

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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.

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