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  • × theme_ss:"Automatisches Abstracting"
  1. Ruda, S.: Maschinenunterstützte Kondensierung von Fachtexten mit CONNY : Abstracting am Beispiel eines 'Nachrichten für Dokumentation'-Textkorpus (1994) 0.01
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    Abstract
    Als Textkorpus sind von 50 verschiedenen Autoren verfaßte Dokumente der Zeitschrift 'Nachrichten für Dokumentation' aus einem Zwanzigjahreszeitraum (1969-1989) herangezogen worden. Die Untersuchung der Abstracts hat ergeben, daß lediglich 15 von 50 Abstracts aus ausschließlich 'normgerechten' Abstractsätzen bestehen und kein Abstract allen Anforderungen der Richtlinien genügt. Insofern signalisieren sie die Abstracting-Richtlinien als 'Wunschdenken', was die Idee des maschinenunterstützten Abstracting nach linguistischen Merkmalen bekräftigt. CONNY ist ein interaktives linhuistisches Abstracting-Modell für Fachtexte, das dem Abstractor auf der Oberflächenstruktur operierende allgemeine Abstracting-Richtlinien anbietet. Es kondendiert die als abstractrelevant bewertenden Primärtextteile auf Primärtext-, Satz- und Abstractebene hinsichtlich Lexik, Syntax und Semantik
  2. Automatic summarizing : introduction (1995) 0.01
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    Content
    Enthält u.a. Beiträge von: J. BATEMAN u. E. TEICH; R. BRANDOW, K. MITZE u. L.F. RAU; B. ENDRES-NIGGEMEYER, E. MAIER u. A. SIGEL; M.T. MAYBURY; K. McKEOWN, J. ROBIN u. K. KUKICH; A. ROTHKEGEL
    Editor
    Sparck Jones, K. u. B. Endres-Niggemeyer
  3. Endres-Niggemeyer, B.: Kognitive Modellierung des Abstracting (1991) 0.01
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    Source
    Deutscher Dokumentartag 1990. 1. Deutsch-deutscher Dokumentartag, 25.-27.9.90, Fulda. Proceedings. Hrsg. W. Neubauer u. U. Schneider-Briehn
  4. Hahn, U.: Automatisches Abstracting (2013) 0.01
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    Source
    Grundlagen der praktischen Information und Dokumentation. Handbuch zur Einführung in die Informationswissenschaft und -praxis. 6., völlig neu gefaßte Ausgabe. Hrsg. von R. Kuhlen, W. Semar u. D. Strauch. Begründet von Klaus Laisiepen, Ernst Lutterbeck, Karl-Heinrich Meyer-Uhlenried
  5. Endres-Niggemeyer, B.: ¬An empirical process model of abstracting (1992) 0.01
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    Source
    Mensch und Maschine: Informationelle Schnittstellen der Kommunikation. Proc. des 3. Int. Symposiums für Informationswissenschaft (ISI'92), 5.-7.11.1992 in Saarbrücken. Hrsg.: H.H. Zimmermann, H.-D. Luckhardt u. A. Schulz
  6. Johnson, F.C.; Paice, C.D.; Black, W.J.; Neal, A.P.: ¬The application of linguistic processing to automatic abstract generation (1993) 0.01
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.538-552.
  7. Salton, G.; Allan, J.; Buckley, C.; Singhal, A.: Automatic analysis, theme generation, and summarization of machine readable texts (1994) 0.01
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.478-483.
  8. Marsh, E.: ¬A production rule system for message summarisation (1984) 0.01
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.534-537.
  9. Advances in automatic text summarization (1999) 0.01
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    Editor
    Mani, I. u. M.T. Maybury
  10. Hahn, U.: ¬Die Verdichtung textuellen Wissens zu Information : vom Wandel methodischer Paradigmen beim automatischen Abstracting (2004) 0.01
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  11. Meyer, R.: Allein, es wär' so schön gewesen : Der Copernic Summarzier kann Internettexte leider nicht befriedigend und sinnvoll zusammenfassen (2002) 0.01
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    Source
    Frankfurter Allgemeine Zeitung. Nr.xxx vom 9.7.2002, S.xx
  12. Ruda, S.: Abstracting: eine Auswahlbibliographie (1992) 0.01
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    Abstract
    Die vorliegende Auswahlbibliographie ist in 9 Themenbereiche unterteilt. Der erste Abschnitt enthält Literatur, in der auf Abstracts und Abstracting-Verfahren allgemein eingegangen und ein Überblick über den Stand der Forschung gegeben wird. Im nächsten Abschnitt werden solche Aufsätze referiert, die die historische Entwicklung des Abstracting beschreiben. Im dritten Teil sind Abstracting-Richtlinien verschiedener Institutionen aufgelistet. Lexikalische, syntaktische und semantische Textkondensierungsverfahren sind das Thema der in Abschnitt 4 präsentierten Arbeiten. Textstrukturen von Abstracts werden unter Punkt 5 betrachtet, und die Arbeiten des nächsten Themenbereiches befassen sich mit dem Problem des Schreibens von Abstracts. Der siebte Abschnitt listet sog. 'maschinelle' und maschinen-unterstützte Abstracting-Methoden auf. Anschließend werden 'maschinelle' und maschinenunterstützte Abstracting-Verfahren, Abstracts im Vergleich zu ihren Primärtexten sowie Abstracts im allgemeien bewertet. Den Abschluß bilden Bibliographien
  13. Endres-Niggemeyer, B.; Jauris-Heipke, S.; Pinsky, S.M.; Ulbricht, U.: Wissen gewinnen durch Wissen : Ontologiebasierte Informationsextraktion (2006) 0.00
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  14. Goh, A.; Hui, S.C.: TES: a text extraction system (1996) 0.00
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    Date
    26. 2.1997 10:22:43
  15. Robin, J.; McKeown, K.: Empirically designing and evaluating a new revision-based model for summary generation (1996) 0.00
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    Date
    6. 3.1997 16:22:15
  16. Jones, P.A.; Bradbeer, P.V.G.: Discovery of optimal weights in a concept selection system (1996) 0.00
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    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  17. Kuhlen, R.: Informationsaufbereitung III : Referieren (Abstracts - Abstracting - Grundlagen) (2004) 0.00
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    Source
    Grundlagen der praktischen Information und Dokumentation. 5., völlig neu gefaßte Ausgabe. 2 Bde. Hrsg. von R. Kuhlen, Th. Seeger u. D. Strauch. Begründet von Klaus Laisiepen, Ernst Lutterbeck, Karl-Heinrich Meyer-Uhlenried. Bd.1: Handbuch zur Einführung in die Informationswissenschaft und -praxis
  18. Vanderwende, L.; Suzuki, H.; Brockett, J.M.; Nenkova, A.: Beyond SumBasic : task-focused summarization with sentence simplification and lexical expansion (2007) 0.00
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    Abstract
    In recent years, there has been increased interest in topic-focused multi-document summarization. In this task, automatic summaries are produced in response to a specific information request, or topic, stated by the user. The system we have designed to accomplish this task comprises four main components: a generic extractive summarization system, a topic-focusing component, sentence simplification, and lexical expansion of topic words. This paper details each of these components, together with experiments designed to quantify their individual contributions. We include an analysis of our results on two large datasets commonly used to evaluate task-focused summarization, the DUC2005 and DUC2006 datasets, using automatic metrics. Additionally, we include an analysis of our results on the DUC2006 task according to human evaluation metrics. In the human evaluation of system summaries compared to human summaries, i.e., the Pyramid method, our system ranked first out of 22 systems in terms of overall mean Pyramid score; and in the human evaluation of summary responsiveness to the topic, our system ranked third out of 35 systems.
  19. Wu, Y.-f.B.; Li, Q.; Bot, R.S.; Chen, X.: Finding nuggets in documents : a machine learning approach (2006) 0.00
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    Date
    22. 7.2006 17:25:48
  20. Kim, H.H.; Kim, Y.H.: Generic speech summarization of transcribed lecture videos : using tags and their semantic relations (2016) 0.00
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    Date
    22. 1.2016 12:29:41