Mining the biomedical literature

The introduction of high-throughput methods has transformed biology into a data-rich science. Knowledge about biological entities and processes has traditionally been acquired by thousands of scientists through decades of experimentation and analysis. The current abundance of biomedical data is acco...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Shatkay, Hagit [verfasserIn] Craven, Mark [mitwirkender]

Format:	E-Book
Sprache:	Englisch

Erschienen:	Cambridge, Massachusetts: MIT Press ; c2012

Schlagwörter:	Information retrieval Content analysis (Communication) Information storage and retrieval systems ; Biology Information storage and retrieval systems ; Medicine Bioinformatics Medical informatics Data mining Biological literature ; Data processing Medical literature ; Data processing Data Mining Information Storage and Retrieval Medical Informatics

Anmerkung:	Includes bibliographical references and index. - Description based on PDF viewed 12/23/2015
Umfang:	1 PDF (150 pages).
Beschreibung:	Mode of access: World Wide Web.

Reihe:	Computational molecular biology

Links:	Link aufrufen Link aufrufen
ISBN:	978-0-262-30516-7 0-262-01769-5 978-0-262-01769-5

Katalog-ID:	1727348524

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Indexfelder

author_variant	h s hs
matchkey_str	book:9780262305167:2012----
oclc_num	850934455
hierarchy_sort_str	c2012
publishDate	2012
allfields	9780262305167 electronic 978-0-262-30516-7 0262017695 0-262-01769-5 9780262017695 978-0-262-01769-5 (DE-627)1727348524 (DE-599)KEP055121683 (OCoLC)850934455 (MITPRESS)6354187 (EBP)055121683 DE-627 ger DE-627 rda eng 610.285 23 Shatkay, Hagit verfasserin aut Mining the biomedical literature Hagit Shatkay and Mark Craven Cambridge, Massachusetts MIT Press c2012 1 PDF (150 pages). Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Computational molecular biology Includes bibliographical references and index. - Description based on PDF viewed 12/23/2015 The introduction of high-throughput methods has transformed biology into a data-rich science. Knowledge about biological entities and processes has traditionally been acquired by thousands of scientists through decades of experimentation and analysis. The current abundance of biomedical data is accompanied by the creation and quick dissemination of new information. Much of this information and knowledge, however, is represented only in text form--in the biomedical literature, lab notebooks, Web pages, and other sources. Researchers' need to find relevant information in the vast amounts of text has created a surge of interest in automated text-analysis.In this book, Hagit Shatkay and Mark Craven offer a concise and accessible introduction to key ideas in biomedical text mining. The chapters cover such topics as the relevant sources of biomedical text; text-analysis methods in natural language processing; the tasks of information extraction, information retrieval, and text categorization; and methods for empirically assessing text-mining systems. Finally, the authors describe several applications that recognize entities in text and link them to other entities and data resources, support the curation of structured databases, and make use of text to enable further prediction and discovery. Mode of access: World Wide Web. Information retrieval Content analysis (Communication) Information storage and retrieval systems ; Biology Information storage and retrieval systems ; Medicine Bioinformatics Medical informatics Data mining Biological literature ; Data processing Medical literature ; Data processing Data Mining Information Storage and Retrieval Medical Informatics Craven, Mark mitwirkender ctb 9780262017695 Erscheint auch als Druck-Ausgabe 9780262017695 https://ieeexplore.ieee.org/book/6354187 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 BO 045F 610.285 22 01 0018 3848474611 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957240115 olr-MIT i z 23-07-21 100 01 3100 4472467224 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011221511 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740749210 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6354187 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6354187 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6354187 100 01 3100 https://ieeexplore.ieee.org/book/6354187 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6354187 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6354187 2015 01 DE-93 https://ieeexplore.ieee.org/book/6354187 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01
spelling	9780262305167 electronic 978-0-262-30516-7 0262017695 0-262-01769-5 9780262017695 978-0-262-01769-5 (DE-627)1727348524 (DE-599)KEP055121683 (OCoLC)850934455 (MITPRESS)6354187 (EBP)055121683 DE-627 ger DE-627 rda eng 610.285 23 Shatkay, Hagit verfasserin aut Mining the biomedical literature Hagit Shatkay and Mark Craven Cambridge, Massachusetts MIT Press c2012 1 PDF (150 pages). Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Computational molecular biology Includes bibliographical references and index. - Description based on PDF viewed 12/23/2015 The introduction of high-throughput methods has transformed biology into a data-rich science. Knowledge about biological entities and processes has traditionally been acquired by thousands of scientists through decades of experimentation and analysis. The current abundance of biomedical data is accompanied by the creation and quick dissemination of new information. Much of this information and knowledge, however, is represented only in text form--in the biomedical literature, lab notebooks, Web pages, and other sources. Researchers' need to find relevant information in the vast amounts of text has created a surge of interest in automated text-analysis.In this book, Hagit Shatkay and Mark Craven offer a concise and accessible introduction to key ideas in biomedical text mining. The chapters cover such topics as the relevant sources of biomedical text; text-analysis methods in natural language processing; the tasks of information extraction, information retrieval, and text categorization; and methods for empirically assessing text-mining systems. Finally, the authors describe several applications that recognize entities in text and link them to other entities and data resources, support the curation of structured databases, and make use of text to enable further prediction and discovery. Mode of access: World Wide Web. Information retrieval Content analysis (Communication) Information storage and retrieval systems ; Biology Information storage and retrieval systems ; Medicine Bioinformatics Medical informatics Data mining Biological literature ; Data processing Medical literature ; Data processing Data Mining Information Storage and Retrieval Medical Informatics Craven, Mark mitwirkender ctb 9780262017695 Erscheint auch als Druck-Ausgabe 9780262017695 https://ieeexplore.ieee.org/book/6354187 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 BO 045F 610.285 22 01 0018 3848474611 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957240115 olr-MIT i z 23-07-21 100 01 3100 4472467224 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011221511 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740749210 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6354187 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6354187 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6354187 100 01 3100 https://ieeexplore.ieee.org/book/6354187 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6354187 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6354187 2015 01 DE-93 https://ieeexplore.ieee.org/book/6354187 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01
allfields_unstemmed	9780262305167 electronic 978-0-262-30516-7 0262017695 0-262-01769-5 9780262017695 978-0-262-01769-5 (DE-627)1727348524 (DE-599)KEP055121683 (OCoLC)850934455 (MITPRESS)6354187 (EBP)055121683 DE-627 ger DE-627 rda eng 610.285 23 Shatkay, Hagit verfasserin aut Mining the biomedical literature Hagit Shatkay and Mark Craven Cambridge, Massachusetts MIT Press c2012 1 PDF (150 pages). Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Computational molecular biology Includes bibliographical references and index. - Description based on PDF viewed 12/23/2015 The introduction of high-throughput methods has transformed biology into a data-rich science. Knowledge about biological entities and processes has traditionally been acquired by thousands of scientists through decades of experimentation and analysis. The current abundance of biomedical data is accompanied by the creation and quick dissemination of new information. Much of this information and knowledge, however, is represented only in text form--in the biomedical literature, lab notebooks, Web pages, and other sources. Researchers' need to find relevant information in the vast amounts of text has created a surge of interest in automated text-analysis.In this book, Hagit Shatkay and Mark Craven offer a concise and accessible introduction to key ideas in biomedical text mining. The chapters cover such topics as the relevant sources of biomedical text; text-analysis methods in natural language processing; the tasks of information extraction, information retrieval, and text categorization; and methods for empirically assessing text-mining systems. Finally, the authors describe several applications that recognize entities in text and link them to other entities and data resources, support the curation of structured databases, and make use of text to enable further prediction and discovery. Mode of access: World Wide Web. Information retrieval Content analysis (Communication) Information storage and retrieval systems ; Biology Information storage and retrieval systems ; Medicine Bioinformatics Medical informatics Data mining Biological literature ; Data processing Medical literature ; Data processing Data Mining Information Storage and Retrieval Medical Informatics Craven, Mark mitwirkender ctb 9780262017695 Erscheint auch als Druck-Ausgabe 9780262017695 https://ieeexplore.ieee.org/book/6354187 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 BO 045F 610.285 22 01 0018 3848474611 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957240115 olr-MIT i z 23-07-21 100 01 3100 4472467224 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011221511 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740749210 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6354187 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6354187 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6354187 100 01 3100 https://ieeexplore.ieee.org/book/6354187 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6354187 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6354187 2015 01 DE-93 https://ieeexplore.ieee.org/book/6354187 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01
allfieldsGer	9780262305167 electronic 978-0-262-30516-7 0262017695 0-262-01769-5 9780262017695 978-0-262-01769-5 (DE-627)1727348524 (DE-599)KEP055121683 (OCoLC)850934455 (MITPRESS)6354187 (EBP)055121683 DE-627 ger DE-627 rda eng 610.285 23 Shatkay, Hagit verfasserin aut Mining the biomedical literature Hagit Shatkay and Mark Craven Cambridge, Massachusetts MIT Press c2012 1 PDF (150 pages). Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Computational molecular biology Includes bibliographical references and index. - Description based on PDF viewed 12/23/2015 The introduction of high-throughput methods has transformed biology into a data-rich science. Knowledge about biological entities and processes has traditionally been acquired by thousands of scientists through decades of experimentation and analysis. The current abundance of biomedical data is accompanied by the creation and quick dissemination of new information. Much of this information and knowledge, however, is represented only in text form--in the biomedical literature, lab notebooks, Web pages, and other sources. Researchers' need to find relevant information in the vast amounts of text has created a surge of interest in automated text-analysis.In this book, Hagit Shatkay and Mark Craven offer a concise and accessible introduction to key ideas in biomedical text mining. The chapters cover such topics as the relevant sources of biomedical text; text-analysis methods in natural language processing; the tasks of information extraction, information retrieval, and text categorization; and methods for empirically assessing text-mining systems. Finally, the authors describe several applications that recognize entities in text and link them to other entities and data resources, support the curation of structured databases, and make use of text to enable further prediction and discovery. Mode of access: World Wide Web. Information retrieval Content analysis (Communication) Information storage and retrieval systems ; Biology Information storage and retrieval systems ; Medicine Bioinformatics Medical informatics Data mining Biological literature ; Data processing Medical literature ; Data processing Data Mining Information Storage and Retrieval Medical Informatics Craven, Mark mitwirkender ctb 9780262017695 Erscheint auch als Druck-Ausgabe 9780262017695 https://ieeexplore.ieee.org/book/6354187 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 BO 045F 610.285 22 01 0018 3848474611 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957240115 olr-MIT i z 23-07-21 100 01 3100 4472467224 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011221511 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740749210 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6354187 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6354187 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6354187 100 01 3100 https://ieeexplore.ieee.org/book/6354187 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6354187 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6354187 2015 01 DE-93 https://ieeexplore.ieee.org/book/6354187 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01
allfieldsSound	9780262305167 electronic 978-0-262-30516-7 0262017695 0-262-01769-5 9780262017695 978-0-262-01769-5 (DE-627)1727348524 (DE-599)KEP055121683 (OCoLC)850934455 (MITPRESS)6354187 (EBP)055121683 DE-627 ger DE-627 rda eng 610.285 23 Shatkay, Hagit verfasserin aut Mining the biomedical literature Hagit Shatkay and Mark Craven Cambridge, Massachusetts MIT Press c2012 1 PDF (150 pages). Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Computational molecular biology Includes bibliographical references and index. - Description based on PDF viewed 12/23/2015 The introduction of high-throughput methods has transformed biology into a data-rich science. Knowledge about biological entities and processes has traditionally been acquired by thousands of scientists through decades of experimentation and analysis. The current abundance of biomedical data is accompanied by the creation and quick dissemination of new information. Much of this information and knowledge, however, is represented only in text form--in the biomedical literature, lab notebooks, Web pages, and other sources. Researchers' need to find relevant information in the vast amounts of text has created a surge of interest in automated text-analysis.In this book, Hagit Shatkay and Mark Craven offer a concise and accessible introduction to key ideas in biomedical text mining. The chapters cover such topics as the relevant sources of biomedical text; text-analysis methods in natural language processing; the tasks of information extraction, information retrieval, and text categorization; and methods for empirically assessing text-mining systems. Finally, the authors describe several applications that recognize entities in text and link them to other entities and data resources, support the curation of structured databases, and make use of text to enable further prediction and discovery. Mode of access: World Wide Web. Information retrieval Content analysis (Communication) Information storage and retrieval systems ; Biology Information storage and retrieval systems ; Medicine Bioinformatics Medical informatics Data mining Biological literature ; Data processing Medical literature ; Data processing Data Mining Information Storage and Retrieval Medical Informatics Craven, Mark mitwirkender ctb 9780262017695 Erscheint auch als Druck-Ausgabe 9780262017695 https://ieeexplore.ieee.org/book/6354187 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP SSG-OLC-PHA GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 BO 045F 610.285 22 01 0018 3848474611 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 3957240115 olr-MIT i z 23-07-21 100 01 3100 4472467224 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011221511 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740749210 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6354187 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6354187 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6354187 100 01 3100 https://ieeexplore.ieee.org/book/6354187 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6354187 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6354187 2015 01 DE-93 https://ieeexplore.ieee.org/book/6354187 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01
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spellingShingle	Shatkay, Hagit ddc 610.285 misc Information retrieval misc Content analysis (Communication) misc Information storage and retrieval systems ; Biology misc Information storage and retrieval systems ; Medicine misc Bioinformatics misc Medical informatics misc Data mining misc Biological literature ; Data processing misc Medical literature ; Data processing misc Data Mining misc Information Storage and Retrieval misc Medical Informatics Mining the biomedical literature
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topic_title	610.285 23 Mining the biomedical literature Hagit Shatkay and Mark Craven Information retrieval Content analysis (Communication) Information storage and retrieval systems ; Biology Information storage and retrieval systems ; Medicine Bioinformatics Medical informatics Data mining Biological literature ; Data processing Medical literature ; Data processing Data Mining Information Storage and Retrieval Medical Informatics
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publisherStr	MIT Press
topic	ddc 610.285 misc Information retrieval misc Content analysis (Communication) misc Information storage and retrieval systems ; Biology misc Information storage and retrieval systems ; Medicine misc Bioinformatics misc Medical informatics misc Data mining misc Biological literature ; Data processing misc Medical literature ; Data processing misc Data Mining misc Information Storage and Retrieval misc Medical Informatics
topic_unstemmed	ddc 610.285 misc Information retrieval misc Content analysis (Communication) misc Information storage and retrieval systems ; Biology misc Information storage and retrieval systems ; Medicine misc Bioinformatics misc Medical informatics misc Data mining misc Biological literature ; Data processing misc Medical literature ; Data processing misc Data Mining misc Information Storage and Retrieval misc Medical Informatics
topic_browse	ddc 610.285 misc Information retrieval misc Content analysis (Communication) misc Information storage and retrieval systems ; Biology misc Information storage and retrieval systems ; Medicine misc Bioinformatics misc Medical informatics misc Data mining misc Biological literature ; Data processing misc Medical literature ; Data processing misc Data Mining misc Information Storage and Retrieval misc Medical Informatics
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abstract	The introduction of high-throughput methods has transformed biology into a data-rich science. Knowledge about biological entities and processes has traditionally been acquired by thousands of scientists through decades of experimentation and analysis. The current abundance of biomedical data is accompanied by the creation and quick dissemination of new information. Much of this information and knowledge, however, is represented only in text form--in the biomedical literature, lab notebooks, Web pages, and other sources. Researchers' need to find relevant information in the vast amounts of text has created a surge of interest in automated text-analysis.In this book, Hagit Shatkay and Mark Craven offer a concise and accessible introduction to key ideas in biomedical text mining. The chapters cover such topics as the relevant sources of biomedical text; text-analysis methods in natural language processing; the tasks of information extraction, information retrieval, and text categorization; and methods for empirically assessing text-mining systems. Finally, the authors describe several applications that recognize entities in text and link them to other entities and data resources, support the curation of structured databases, and make use of text to enable further prediction and discovery. Includes bibliographical references and index. - Description based on PDF viewed 12/23/2015
abstractGer	The introduction of high-throughput methods has transformed biology into a data-rich science. Knowledge about biological entities and processes has traditionally been acquired by thousands of scientists through decades of experimentation and analysis. The current abundance of biomedical data is accompanied by the creation and quick dissemination of new information. Much of this information and knowledge, however, is represented only in text form--in the biomedical literature, lab notebooks, Web pages, and other sources. Researchers' need to find relevant information in the vast amounts of text has created a surge of interest in automated text-analysis.In this book, Hagit Shatkay and Mark Craven offer a concise and accessible introduction to key ideas in biomedical text mining. The chapters cover such topics as the relevant sources of biomedical text; text-analysis methods in natural language processing; the tasks of information extraction, information retrieval, and text categorization; and methods for empirically assessing text-mining systems. Finally, the authors describe several applications that recognize entities in text and link them to other entities and data resources, support the curation of structured databases, and make use of text to enable further prediction and discovery. Includes bibliographical references and index. - Description based on PDF viewed 12/23/2015
abstract_unstemmed	The introduction of high-throughput methods has transformed biology into a data-rich science. Knowledge about biological entities and processes has traditionally been acquired by thousands of scientists through decades of experimentation and analysis. The current abundance of biomedical data is accompanied by the creation and quick dissemination of new information. Much of this information and knowledge, however, is represented only in text form--in the biomedical literature, lab notebooks, Web pages, and other sources. Researchers' need to find relevant information in the vast amounts of text has created a surge of interest in automated text-analysis.In this book, Hagit Shatkay and Mark Craven offer a concise and accessible introduction to key ideas in biomedical text mining. The chapters cover such topics as the relevant sources of biomedical text; text-analysis methods in natural language processing; the tasks of information extraction, information retrieval, and text categorization; and methods for empirically assessing text-mining systems. Finally, the authors describe several applications that recognize entities in text and link them to other entities and data resources, support the curation of structured databases, and make use of text to enable further prediction and discovery. Includes bibliographical references and index. - Description based on PDF viewed 12/23/2015
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title_short	Mining the biomedical literature
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