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Titel: Text skimming as a part in paper document understanding
Verfasser: Bleisinger, Rainer
Gores, Klaus-Peter
Sprache: Englisch
Erscheinungsjahr: 1994
Quelle: Kaiserslautern ; Saarbrücken : DFKI, 1994
SWD-Schlagwörter: Künstliche Intelligenz
DDC-Sachgruppe: 004 Informatik
Dokumentart : Report (Bericht)
Kurzfassung: In our document understanding project ALV we analyse incoming paper mail in the domain of single-sided German business letters. These letters are scanned and after several analysis steps the text is recognized. The result may contain gaps, word alternatives, and even illegal words. The subject of this paper is the subsequent phase which concerns the extraction of important information predefined in our "message type model". An expectation driven partial text skimming analysis is proposed focussing on the kernel module, the so-called "predictor". In contrast to traditional text skimming the following aspects are important in our approach. Basically, the input data are fragmentary texts. Rather than having one text analysis module ("substantiator") only, our predictor controls a set of different and partially alternative substantiators. With respect to the usually proposed three working phases of a predictor - start, discrimination, and instantiation - the following differences are remarkable. The starting problem of text skimming is solved by applying specialized substantiators for classifying a business letter into message types. In order to select appropriate expectations within the message type hypotheses a twofold discrimination is performed. A coarse discrimination reduces the number of message type alternatives, and a fine discrimination chooses one expectation within one or a few previously selected message types. According to the expectation selected substantiators are activated. Several rules are applied both for the verification of the substantiator results and for error recovery if the results are insufficient.
Link zu diesem Datensatz: urn:nbn:de:bsz:291-scidok-38979
Schriftenreihe: Technical memo / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-0071]
Band: 94-01
SciDok-Publikation: 8-Jul-2011
Fakultät: SE - Sonstige Einrichtungen
Fachrichtung: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Fakultät / Institution:SciDok - Elektronische Dokumente der UdS

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