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  • 1
    UID:
    almafu_9959763227102883
    Umfang: 1 online resource (xiii, 126 pages).
    Ausgabe: 1st ed. 2020.
    ISBN: 9783030464936 , 3030464938
    Serie: Palgrave pivot
    Inhalt: “McGillivray and Tóth provide a very comprehensible introduction to the most important current approaches of computer-aided text analysis in the Digital Humanities. By giving illustrative examples and many practical tips, they let the reader participate in their vast experience in this quickly evolving field of research.”--Gregor Wiedemann, University of Hamburg, Germany This book presents established and state-of-the-art methods in Language Technology (including text mining, corpus linguistics, computational linguistics, and natural language processing), and demonstrates how they can be applied by humanities scholars working with textual data. The landscape of humanities research has recently changed thanks to the proliferation of big data and large textual collections such as Google Books, Early English Books Online, and Project Gutenberg. These resources have yet to be fully explored by new generations of scholars, and the authors argue that Language Technology has a key role to play in the exploration of large-scale textual data. The authors use a series of illustrative examples from various humanistic disciplines (mainly but not exclusively from History, Classics, and Literary Studies) to demonstrate basic and more complex use-case scenarios. This book will be useful to graduate students and researchers in humanistic disciplines working with textual data, including History, Modern Languages, Literary studies, Classics, and Linguistics. This is also a very useful book for anyone teaching or learning Digital Humanities and interested in the basic concepts from computational linguistics, corpus linguistics, and natural language processing. Barbara McGillivray is a Turing Research Fellow at the University of Cambridge and The Alan Turing Institute, UK. She has published two monographs, Methods in Latin Computational Linguistics (2014) and Quantitative Historical Linguistics. A corpus framework (2017). Gábor Mihály Tóth is a Research Fellow at the USC Shoah Foundation and the Signal Analysis and Interpretation Laboratory (SAIL), Viterbi School of Engineering, University of Southern California, USA.
    Anmerkung: Includes index. , Chapter 1: Language Technology for the Humanities -- Chapter 2: Design of Text Resources and Tools -- Chapter 3: Frequency -- Chapter 4: Collocation -- Chapter 5: Word Meaning in Texts -- Chapter 6: Mining Textual Collections -- Chapter 7: Closing Remarks. .
    Weitere Ausg.: ISBN 9783030464929
    Weitere Ausg.: ISBN 303046492X
    Sprache: Englisch
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 2
    UID:
    gbv_1743998783
    Umfang: xiii, 126 Seiten , Illustrationen, Diagramme , 22 cm
    ISBN: 303046492X , 9783030464929
    Serie: Palgrave pivot
    Inhalt: Chapter 1: Language Technology for the Humanities -- Chapter 2: Design of Text Resources and Tools -- Chapter 3: Frequency -- Chapter 4: Collocation -- Chapter 5: Word Meaning in Texts -- Chapter 6: Mining Textual Collections -- Chapter 7: Closing Remarks.
    Inhalt: "McGillivray and Tóth provide a very comprehensible introduction to the most important current approaches of computer-aided text analysis in the Digital Humanities. By giving illustrative examples and many practical tips, they let the reader participate in their vast experience in this quickly evolving field of research."--Gregor Wiedemann, University of Hamburg, Germany This book presents established and state-of-the-art methods in Language Technology (including text mining, corpus linguistics, computational linguistics, and natural language processing), and demonstrates how they can be applied by humanities scholars working with textual data. The landscape of humanities research has recently changed thanks to the proliferation of big data and large textual collections such as Google Books, Early English Books Online, and Project Gutenberg. These resources have yet to be fully explored by new generations of scholars, and the authors argue that Language Technology has a key role to play in the exploration of large-scale textual data. The authors use a series of illustrative examples from various humanistic disciplines (mainly but not exclusively from History, Classics, and Literary Studies) to demonstrate basic and more complex use-case scenarios. This book will be useful to graduate students and researchers in humanistic disciplines working with textual data, including History, Modern Languages, Literary studies, Classics, and Linguistics. This is also a very useful book for anyone teaching or learning Digital Humanities and interested in the basic concepts from computational linguistics, corpus linguistics, and natural language processing. Barbara McGillivray is a Turing Research Fellow at the University of Cambridge and The Alan Turing Institute, UK. She has published two monographs, Methods in Latin Computational Linguistics (2014) and Quantitative Historical Linguistics. A corpus framework (2017). Gábor Mihály Tóth is a Research Fellow at the USC Shoah Foundation and the Signal Analysis and Interpretation Laboratory (SAIL), Viterbi School of Engineering, University of Southern California, USA
    Anmerkung: Includes bibliographical references and index
    Weitere Ausg.: ISBN 9783030464936
    Weitere Ausg.: Erscheint auch als Online-Ausgabe McGillivray, Barbara Applying language technology in humanities research Cham : Springer, 2020 ISBN 9783030464936
    Sprache: Englisch
    Schlagwort(e): Digital Humanities ; Computerlinguistik ; Korpus ; Natürlichsprachiges System
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 3
    UID:
    almahu_BV046835477
    Umfang: 1 Online-Ressource (xiii, 126 Seiten) : , Illustrationen, Diagramme.
    ISBN: 978-3-030-46493-6
    Serie: Palgrave pivot
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-46492-9
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-46494-3
    Sprache: Englisch
    Schlagwort(e): Linguistik ; Digital Humanities ; Data Mining
    URL: Volltext  (URL des Erstveröffentlichers)
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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