Search (15 results, page 1 of 1)

  • × theme_ss:"Automatisches Abstracting"
  1. Kuhlen, R.: Abstracts, abstracting : intellektuelle und maschinelle Verfahren (1997) 0.02
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    Year
    1997
  2. Salton, G.: Automatic text structuring and summarization (1997) 0.02
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    Source
    Information processing and management. 33(1997) no.2, S.193-207
    Year
    1997
  3. Johnson, F.C.; Paice, C.D.; Black, W.J.; Neal, A.P.: ¬The application of linguistic processing to automatic abstract generation (1993) 0.02
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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.
  4. Salton, G.; Allan, J.; Buckley, C.; Singhal, A.: Automatic analysis, theme generation, and summarization of machine readable texts (1994) 0.02
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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.
  5. Marsh, E.: ¬A production rule system for message summarisation (1984) 0.02
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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.
  6. Moens, M.-F.; Uyttendaele, C.: Automatic text structuring and categorization as a first step in summarizing legal cases (1997) 0.02
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    Source
    Information processing and management. 33(1997) no.6, S.727-737
    Year
    1997
  7. Goh, A.; Hui, S.C.: TES: a text extraction system (1996) 0.01
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    Date
    26. 2.1997 10:22:43
  8. Robin, J.; McKeown, K.: Empirically designing and evaluating a new revision-based model for summary generation (1996) 0.01
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    Date
    6. 3.1997 16:22:15
  9. 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
  10. Marcu, D.: Automatic abstracting and summarization (2009) 0.01
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    Abstract
    After lying dormant for a few decades, the field of automated text summarization has experienced a tremendous resurgence of interest. Recently, many new algorithms and techniques have been proposed for identifying important information in single documents and document collections, and for mapping this information into grammatical, cohesive, and coherent abstracts. Since 1997, annual workshops, conferences, and large-scale comparative evaluations have provided a rich environment for exchanging ideas between researchers in Asia, Europe, and North America. This entry reviews the main developments in the field and provides a guiding map to those interested in understanding the strengths and weaknesses of an increasingly ubiquitous technology.
  11. Vanderwende, L.; Suzuki, H.; Brockett, J.M.; Nenkova, A.: Beyond SumBasic : task-focused summarization with sentence simplification and lexical expansion (2007) 0.01
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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.
  12. Wu, Y.-f.B.; Li, Q.; Bot, R.S.; Chen, X.: Finding nuggets in documents : a machine learning approach (2006) 0.01
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    Date
    22. 7.2006 17:25:48
  13. 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
  14. 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
  15. Jiang, Y.; Meng, R.; Huang, Y.; Lu, W.; Liu, J.: Generating keyphrases for readers : a controllable keyphrase generation framework (2023) 0.01
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    Date
    22. 6.2023 14:55:20