Livre: Piotrowski, Natural Language Processing for Historical Texts

[Thierry Hamon]

Date: Fri, 23 Nov 2012 15:56:21 -0500
From: Graeme Hirst <gh at cs.toronto.edu>
Message-Id: <B77B62E9-43CC-46F8-9BE6-C8A9CCC3E67B at cs.toronto.edu>
X-url: http://www.morganclaypool.com/doi/pdf/10.2200/S00436ED1V01Y201207HLT017
X-url: http://www.morganclaypool.com/page/licensed


NEW BOOK

Natural Language Processing for Historical Texts
by Michael Piotrowski, Leibniz Institute of European History, Germany

Synthesis Lectures on Human Language Technologies #17
(Morgan & Claypool Publishers), 2012, 157 pages

Abstract

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

http://www.morganclaypool.com/doi/pdf/10.2200/S00436ED1V01Y201207HLT017

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