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Automated postcorrection of OCRed historical printings with integrated optional interactive postcorrection

Automated postcorrection of OCRed historical printings with integrated optional interactive postcorrection
通过集成的可选交互式后期校正对 ORed 历史打印进行自动后期校正
批准号:
393215159
负责人:
Professor Dr. Klaus U. Schulz
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research data and software (Scientific Library Services and Information Systems)
财政年份:
2018
资助国家:
德国
项目状态:
已结题
起止时间:
2017-12-31 至 2019-12-31

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中文摘要
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英文摘要
The obvious need to improve current methods for full-text digitalization of historical printings represents the general background of the DFG-program ,,Skalierbare Verfahren der Text- und Strukturerkennung für die Volltextdigitalisierung historischer Drucke``. Module 3 of this program in particular explains the need for high-level postcorrection of the OCR output. In our team we developed over several years a specialized system "PoCoTo" for the interactive postcorrection of OCRed historical printings. Still, in the context of mass digitization for obvious reasons systems for automated postcorrection are clearly preferable. The main problem for automated postcorrection is to avoid a replacement of correct OCR-tokens that are not covered by the background correction dictionary. Building up on PoCoTo we want to develop an advanced system for automated postcorrection that largely avoids such ``infelicitous correction steps''. To this end, the PoCoTo background technology will be substantially extended. Since a fully automated postcorrection will not always reach the very high quality standards needed, the automated correction can be completed by an optional semi-automated or interactive postcorrection. Methods for semi-automated or interactive postcorrection that take advantage of all data and insights from the automated correction phase will be directly integrated as part of the system.
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Training of machine-learning based procedures for automated postcorrection of OCRed historical printings
Development of a web-based system for the postcorrection of historical OCR'ed texts
  • 批准号:
    314731081
  • 项目类别:
    Research data and software (Scientific Library Services and Information Systems)
  • 资助金额:
    $0.0万
  • 财政年份:
    2016
  • 负责人:
    Professor Dr. Klaus U. Schulz
  • 依托单位:
Domänen- und dokumentenadaptive Verfahren zur Nachkorrektur von OCR-Ergebnissen
Erweiterung eines Abfragemodells für XML-Daten zur interaktiven Exploration
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