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Natural Language Processing for Historical Texts (Paperback)
Loot Price: R1,202
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Natural Language Processing for Historical Texts (Paperback)
Series: Synthesis Lectures on Human Language Technologies
Expected to ship within 10 - 15 working days
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More 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 and Annotation Schemes / Handling Spelling
Variation / NLP Tools for Historical Languages / Historical Corpora
/ Conclusion / Bibliography
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