Search (38 results, page 1 of 2)

  • × theme_ss:"Automatisches Abstracting"
  1. Robin, J.; McKeown, K.: Empirically designing and evaluating a new revision-based model for summary generation (1996) 0.04 
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    Date
    6. 3.1997 16:22:15
  2. Vanderwende, L.; Suzuki, H.; Brockett, J.M.; Nenkova, A.: Beyond SumBasic : task-focused summarization with sentence simplification and lexical expansion (2007) 0.03 
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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.
    Source
    Information processing and management. 43(2007) no.6, S.1606-1618
  3. Wu, Y.-f.B.; Li, Q.; Bot, R.S.; Chen, X.: Finding nuggets in documents : a machine learning approach (2006) 0.03 
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    Date
    22. 7.2006 17:25:48
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.6, S.740-752
  4. Endres-Niggemeyer, B.; Neugebauer, E.: Professional summarizing : no cognitive simulation without observation (1998) 0.02 
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    Abstract
    Develops a cognitive model of expert summarization, using 54 working processes of 6 experts recorded by thinking-alound protocols. It comprises up to 140 working steps. Components of the model are a toolbox of empirically founded strategies, principles of process organization, and interpreted working steps where the interaction of cognitive strategies can be investigated. In the computerized simulation the SimSum (Simulation of Summarizing) system, cognitive strategies are represented by object-oriented agents grouped around dedicated blckboards
    Date
    6. 3.1999 13:24:07
    Source
    Journal of the American Society for Information Science. 49(1998) no.6, S.486-506
  5. Endres-Niggemeyer, B.: Kognitive Modellierung des Abstracting (1991) 0.01 
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    Date
    6. 1.1999 10:27:10
  6. Goh, A.; Hui, S.C.: TES: a text extraction system (1996) 0.01 
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    Date
    26. 2.1997 10:22:43
  7. Jones, P.A.; Bradbeer, P.V.G.: Discovery of optimal weights in a concept selection system (1996) 0.01 
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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
  8. 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
  9. Xianghao, G.; Yixin, Z.; Li, Y.: ¬A new method of news test understanding and abstracting based on speech acts theory (1998) 0.01 
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    Date
    6. 9.2000 17:21:02
  10. Over, P.; Dang, H.; Harman, D.: DUC in context (2007) 0.01 
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    Source
    Information processing and management. 43(2007) no.6, S.1506-1520
  11. Harabagiu, S.; Hickl, A.; Lacatusu, F.: Satisfying information needs with multi-document summaries (2007) 0.01 
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    Source
    Information processing and management. 43(2007) no.6, S.1619-1642
  12. Sjöbergh, J.: Older versions of the ROUGEeval summarization evaluation system were easier to fool (2007) 0.01 
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    Source
    Information processing and management. 43(2007) no.6, S.1500-1505
  13. Ruda, S.: Maschinenunterstützte Kondensierung von Fachtexten mit CONNY : Abstracting am Beispiel eines 'Nachrichten für Dokumentation'-Textkorpus (1994) 0.01 
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    Source
    Nachrichten für Dokumentation. 45(1994) H.6, S.335-342
  14. Uyttendaele, C.; Moens, M.-F.; Dumortier, J.: SALOMON: automatic abstracting of legal cases for effective access to court decisions (1998) 0.01 
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    Source
    Artificial intelligence and law. 6(1998) no.1, S.59-79
  15. Soricut, R.; Marcu, D.: Abstractive headline generation using WIDL-expressions (2007) 0.01 
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    Source
    Information processing and management. 43(2007) no.6, S.1536-1548
  16. Zajic, D.; Dorr, B.J.; Lin, J.; Schwartz, R.: Multi-candidate reduction : sentence compression as a tool for document summarization tasks (2007) 0.01 
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    Information processing and management. 43(2007) no.6, S.1549-1570
  17. Ercan, G.; Cicekli, I.: Using lexical chains for keyword extraction (2007) 0.01 
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    Information processing and management. 43(2007) no.6, S.1705-1714
  18. Moens, M.-F.: Summarizing court decisions (2007) 0.01 
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    Information processing and management. 43(2007) no.6, S.1748-1764
  19. Kim, H.H.; Kim, Y.H.: Generic speech summarization of transcribed lecture videos : using tags and their semantic relations (2016) 0.01 
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    Date
    22. 1.2016 12:29:41
  20. Oh, H.; Nam, S.; Zhu, Y.: Structured abstract summarization of scientific articles : summarization using full-text section information (2023) 0.01 
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    Date
    22. 1.2023 18:57:12

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