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Machine learning methods for automatically processing historical documents: from paper acquisition to XML transformation | IEEE Conference Publication | IEEE Xplore

Machine learning methods for automatically processing historical documents: from paper acquisition to XML transformation


Abstract:

One of the aims of the EU project COLLATE is to design and implement a Web-based collaboratory for archives, scientists and end-users working with digitized cultural mate...Show More

Abstract:

One of the aims of the EU project COLLATE is to design and implement a Web-based collaboratory for archives, scientists and end-users working with digitized cultural material. Since the originals of such a material are often unique and scattered in various archives, severe problems arise for their wide fruition. A solution would be to develop intelligent document processing tools that automatically transform printed documents into a Web-accessible form such as XML. Here, we propose the use of a document processing system, WISDOM++, which uses heavily machine learning techniques in order to perform such a task, and report promising results obtained in preliminary experiments.
Date of Conference: 23-24 January 2004
Date Added to IEEE Xplore: 24 August 2004
Print ISBN:0-7695-2088-X
Conference Location: Palo Alto, CA, USA

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