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The Four and a Half Challenges of Humanities Data

Xiaoqing Ding, Hiromichi Fujisawa, Jianying Hu (Hrsg). International Conference on Document Analysis and Recognition (ICDAR), 2011. Los Alamitos, CA: IEEE 2011 S. 1017 - 1023

Erscheinungsjahr: 2011

ISBN/ISSN: 978-0-7695-4520-2

Publikationstyp: Diverses (Konferenzbeitrag)

Sprache: Englisch

Doi/URN: 10.1109/ICDAR.2011.206

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Inhaltszusammenfassung


The lead medium of the humanities is text, but text with special characteristics that can be quite different from a normal monolingual article in most modern scripts. Text that can be derived from manuscripts, from retro digitization of previous scholarly publications such as critical editions and dictionaries, from books printed centuries ago, applying conventions no longer in force today. The keynote identifies four major challenges for recognizing humanities data: Unusual characters, unusu...The lead medium of the humanities is text, but text with special characteristics that can be quite different from a normal monolingual article in most modern scripts. Text that can be derived from manuscripts, from retro digitization of previous scholarly publications such as critical editions and dictionaries, from books printed centuries ago, applying conventions no longer in force today. The keynote identifies four major challenges for recognizing humanities data: Unusual characters, unusual layouts, unusual semantics and unusual segmentations. Each challenge is illustrated with concrete examples taken from a variety of times and places, starting with cuneiform tablets, an extract from a Greek manuscript, a page from a multilingual critical edition, a renaissance print, a lemma from a scholarly dictionary, and some more. In addition, scholarly humanities data is typically marked up using domain-specific rich XML-based formats based on the TEI P5 guidelines. Any format that an OCR program produces must be sufficiently rich to permit for a mapping on TEI-compliant markup in order to be capable of reproducing the full richness of the original. A closer view at the Text Grid virtual research environment for the humanities and its Text-Image Link Editor (TBLE) demonstrates how scholars currently tackle these tasks. It analyzes where automatization can facilitate their task and enable new dimensions of research.» weiterlesen» einklappen

  • Layout, Dictionaries, Image segmentation, Optical character recognition software, Semantics, Character recognition, Shape

Autoren


Küster, Marc Wilhelm (Autor)

Klassifikation


DFG Fachgebiet:
Informatik

DDC Sachgruppe:
Informatik