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Report (Bericht) zugänglich unter
URN: urn:nbn:de:bsz:291-scidok-36558
URL: http://scidok.sulb.uni-saarland.de/volltexte/2011/3655/


Document highlighting - message classification in printed business letters

Hoch, Rainer ; Dengel, Andreas

Quelle: (1993) Kaiserslautern ; Saarbrücken : DFKI, 1993
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Dokument 1.pdf (80 KB)

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SWD-Schlagwörter: Künstliche Intelligenz
Institut: DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
DDC-Sachgruppe: Informatik
Dokumentart: Report (Bericht)
Schriftenreihe: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Bandnummer: 93-24
Sprache: Englisch
Erstellungsjahr: 1993
Publikationsdatum: 27.06.2011
Kurzfassung auf Englisch: This paper presents the INFOCLAS system applying statistical methods of information retrieval primarily for the classification of German business letters into corresponding message types such as order, offer, confirmation, etc. INFOCLAS is a first step towards understanding of documents. Actually, it is composed of three modules: the central indexer (extraction and weighting of indexing terms), the classifier (classification of business letters into given types) and the focuser (highlighting relevant letter parts). The system employs several knowledge sources including a database of about 100 letters, word frequency statistics for German, message type specific words, morphological knowledge as well as the underlying document model. As output, the system evaluates a set of weighted hypotheses about the type of letter at hand, or highlights relevant text (text focus), respectively. Classification of documents allows the automatic distribution or archiving of letters and is also an excellent starting point for higher-level document analysis.
Lizenz: Standard-Veröffentlichungsvertrag

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