Please use this identifier to cite or link to this item: doi:10.22028/D291-24899
Title: Document highlighting - message classification in printed business letters
Author(s): Hoch, Rainer
Dengel, Andreas
Language: English
Year of Publication: 1993
OPUS Source: Kaiserslautern ; Saarbrücken : DFKI, 1993
SWD key words: Künstliche Intelligenz
DDC notations: 004 Computer science, internet
Publikation type: Report
Abstract: 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.
Link to this record: urn:nbn:de:bsz:291-scidok-36558
Series name: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Series volume: 93-24
Date of registration: 27-Jun-2011
Faculty: SE - Sonstige Einrichtungen
Department: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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