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- W2078777599 abstract "Automatic information extraction from scanned business documents is especially valuable in the application domain of document archiving. But current systems for automated document processing still require a lot of configuration work that can only be done by experienced users or administrators. We present an approach for information extraction which purely builds on end-user provided training examples and intentionally omits efficient known extraction techniques like rule based extraction that require intense training and/or information extraction expertise. Our evaluation on a large corpus of business documents shows competitive results of above 85% F1-measure on 10 commonly used fields like document type, sender, receiver and date. The system is deployed and used inside the commercial document management system DocuWare." @default.
- W2078777599 created "2016-06-24" @default.
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- W2078777599 date "2013-08-01" @default.
- W2078777599 modified "2023-10-16" @default.
- W2078777599 title "Intellix -- End-User Trained Information Extraction for Document Archiving" @default.
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- W2078777599 doi "https://doi.org/10.1109/icdar.2013.28" @default.
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