000 04305nam a22005175i 4500
001 978-3-031-02146-6
003 DE-He213
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008 220601s2012 sz | s |||| 0|eng d
020 _a9783031021466
_9978-3-031-02146-6
024 7 _a10.1007/978-3-031-02146-6
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aPiotrowski, Michael.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980655
245 1 0 _aNatural Language Processing for Historical Texts
_h[electronic resource] /
_cby Michael Piotrowski.
250 _a1st ed. 2012.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2012.
300 _aXII, 145 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Human Language Technologies,
_x1947-4059
505 0 _aIntroduction -- NLP and Digital Humanities -- Spelling in Historical Texts -- Acquiring Historical Texts -- Text Encoding and Annotation Schemes -- Handling Spelling Variation -- NLP Tools for Historical Languages -- Historical Corpora -- Conclusion -- Bibliography.
520 _aMore and more historical texts are becoming available in digital form. Digitization of paper documents is motivated by the aim of preserving cultural heritage and making it more accessible, both to laypeople and scholars. As digital images cannot be searched for text, digitization projects increasingly strive to create digital text, which can be searched and otherwise automatically processed, in addition to facsimiles. Indeed, the emerging field of digital humanities heavily relies on the availability of digital text for its studies. Together with the increasing availability of historical texts in digital form, there is a growing interest in applying natural language processing (NLP) methods and tools to historical texts. However, the specific linguistic properties of historical texts -- the lack of standardized orthography, in particular -- pose special challenges for NLP. This book aims to give an introduction to NLP for historical texts and an overview of the state of the art in this field. The book starts with an overview of methods for the acquisition of historical texts (scanning and OCR), discusses text encoding and annotation schemes, and presents examples of corpora of historical texts in a variety of languages. The book then discusses specific methods, such as creating part-of-speech taggers for historical languages or handling spelling variation. A final chapter analyzes the relationship between NLP and the digital humanities. Certain recently emerging textual genres, such as SMS, social media, and chat messages, or newsgroup and forum postings share a number of properties with historical texts, for example, nonstandard orthography and grammar, and profuse use of abbreviations. The methods and techniques required for the effective processing of historical texts are thus also of interest for research in other domains. Table of Contents: Introduction / NLP and Digital Humanities / Spelling in Historical Texts / Acquiring Historical Texts / Text Encoding andAnnotation Schemes / Handling Spelling Variation / NLP Tools for Historical Languages / Historical Corpora / Conclusion / Bibliography.
650 0 _aArtificial intelligence.
_93407
650 0 _aNatural language processing (Computer science).
_94741
650 0 _aComputational linguistics.
_96146
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aNatural Language Processing (NLP).
_931587
650 2 4 _aComputational Linguistics.
_96146
710 2 _aSpringerLink (Online service)
_980656
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031010187
776 0 8 _iPrinted edition:
_z9783031032745
830 0 _aSynthesis Lectures on Human Language Technologies,
_x1947-4059
_980657
856 4 0 _uhttps://doi.org/10.1007/978-3-031-02146-6
912 _aZDB-2-SXSC
942 _cEBK
999 _c85006
_d85006