Search (18 results, page 1 of 1)

  • × theme_ss:"Automatisches Abstracting"
  • × language_ss:"e"
  1. Kim, H.H.; Kim, Y.H.: Generic speech summarization of transcribed lecture videos : using tags and their semantic relations (2016) 0.02
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    Date
    22. 1.2016 12:29:41
  2. Oh, H.; Nam, S.; Zhu, Y.: Structured abstract summarization of scientific articles : summarization using full-text section information (2023) 0.02
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    Date
    22. 1.2023 18:57:12
  3. Goh, A.; Hui, S.C.: TES: a text extraction system (1996) 0.01
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    Date
    26. 2.1997 10:22:43
  4. 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
  5. 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
  6. Johnson, F.C.: ¬A critical view of system-centered to user-centered evaluation of automatic abstracting research (1999) 0.01
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    Date
    2.11.1996 12:46:20
  7. Gomez, J.; Allen, K.; Matney, M.; Awopetu, T.; Shafer, S.: Experimenting with a machine generated annotations pipeline (2020) 0.01
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    Date
    12. 5.2020 13:12:58
  8. 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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    Date
    16. 8.1998 12:30:29
  9. 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.
  10. 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
  11. 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
  12. Summarising software for publishing (1996) 0.01
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    Date
    12. 9.1996 13:47:27
  13. Ou, S.; Khoo, C.S.G.; Goh, D.H.: Multi-document summarization of news articles using an event-based framework (2006) 0.00
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    Date
    12. 3.2001 11:34:20
    20. 1.2007 11:55:12
  14. Nomoto, T.: Discriminative sentence compression with conditional random fields (2007) 0.00
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    Date
    26.12.2007 16:12:17
  15. Martinez-Romo, J.; Araujo, L.; Fernandez, A.D.: SemGraph : extracting keyphrases following a novel semantic graph-based approach (2016) 0.00
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    Date
    12. 3.2016 13:38:37
  16. Sweeney, S.; Crestani, F.; Losada, D.E.: 'Show me more' : incremental length summarisation using novelty detection (2008) 0.00
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    Date
    29. 7.2008 19:35:12
  17. Wang, S.; Koopman, R.: Embed first, then predict (2019) 0.00
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    Date
    29. 9.2019 12:18:42
  18. Dunlavy, D.M.; O'Leary, D.P.; Conroy, J.M.; Schlesinger, J.D.: QCS: A system for querying, clustering and summarizing documents (2007) 0.00
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    Date
    26.12.2007 16:14:12