Natural Language Processing for Historical Texts (Paperback)

Michael Piotrowski

  • 出版商: Morgan & Claypool
  • 出版日期: 2012-10-01
  • 定價: $1,575
  • 售價: 9.0$1,418
  • 語言: 英文
  • 頁數: 158
  • 裝訂: Paperback
  • ISBN: 1608459462
  • ISBN-13: 9781608459469
  • 相關分類: 大數據 Big-dataText-mining
  • 立即出貨 (庫存=1)

相關主題

商品描述

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

商品描述(中文翻譯)

越來越多的歷史文本以數位形式提供。將紙質文件數位化的目的是為了保存文化遺產並使其更易於接觸,無論是對一般大眾還是學者。由於數位圖像無法進行文字搜索,數位化項目越來越努力地創建可搜索和自動處理的數位文本,以及其外貌複製品。事實上,新興的數位人文學領域在其研究中極大程度上依賴於數位文本的可用性。

隨著歷史文本以數位形式越來越容易獲得,人們對將自然語言處理(NLP)方法和工具應用於歷史文本的興趣也越來越大。然而,歷史文本的特定語言特性,尤其是缺乏標準化的正字法,對於NLP提出了特殊的挑戰。

本書旨在介紹歷史文本的NLP並概述該領域的最新技術。本書首先概述了歷史文本獲取的方法(掃描和OCR),討論了文本編碼和標註方案,並提供了各種語言的歷史文本語料庫的示例。然後,本書討論了特定的方法,例如為歷史語言創建詞性標記器或處理拼寫變異。最後一章分析了NLP與數位人文學之間的關係。

某些最近出現的文本類型,例如短信、社交媒體和聊天消息,或新聞組和論壇帖子,與歷史文本具有一些共同特點,例如非標準的正字法和語法,以及大量使用縮寫。因此,有效處理歷史文本所需的方法和技術對於其他領域的研究也具有興趣。

目錄:引言 / NLP與數位人文學 / 歷史文本的拼寫 / 獲取歷史文本 / 文本編碼和標註方案 / 處理拼寫變異 / 歷史語言的NLP工具 / 歷史語料庫 / 結論 / 參考文獻