Search (35 results, page 1 of 2)

  • × theme_ss:"Automatisches Abstracting"
  • × language_ss:"e"
  1. Endres-Niggemeyer, B.: ¬An empirical process model of abstracting (1992) 0.01
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    Series
    Schriften zur Informationswissenschaft; Bd.7
    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
  2. Goh, A.; Hui, S.C.: TES: a text extraction system (1996) 0.00
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    Date
    26. 2.1997 10:22:43
    Source
    Microcomputers for information management. 13(1996) no.1, S.41-55
  3. 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
    Source
    Artificial intelligence. 85(1996) nos.1/2, S.135-179
  4. Uyttendaele, C.; Moens, M.-F.; Dumortier, J.: SALOMON: automatic abstracting of legal cases for effective access to court decisions (1998) 0.00
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    Date
    17. 7.1996 14:16:29
    Source
    Artificial intelligence and law. 6(1998) no.1, S.59-79
  5. 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
  6. Pinto, M.: Engineering the production of meta-information : the abstracting concern (2003) 0.00
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    Date
    27.11.2005 18:29:55
    Source
    Journal of information science. 29(2003) no.5, S.405-418
  7. Saggion, H.; Lapalme, G.: Selective analysis for the automatic generation of summaries (2000) 0.00
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    Date
    1. 1.2002 19:40:30
    Source
    Dynamism and stability in knowledge organization: Proceedings of the 6th International ISKO-Conference, 10-13 July 2000, Toronto, Canada. Ed.: C. Beghtol et al
  8. Goh, A.; Hui, S.C.; Chan, S.K.: ¬A text extraction system for news reports (1996) 0.00
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    Abstract
    Describes the design and implementation of a text extraction tool, NEWS_EXT, which aztomatically produces summaries from news reports by extracting sentences to form indicative abstracts. Selection of sentences is based on sentence importance, measured by means of sentence scoring or simple linguistic analysis of sentence structure. Tests were conducted on 4 approaches for the functioning of the NEWS_EXT system; extraction by keyword frequency; extraction by title keywords; extraction by location; and extraction by indicative phrase. Reports results of a study to compare the results of the application of NEWS_EXT with manually produced extracts; using relevance as the criterion for effectiveness. 48 newspaper articles were assessed (The Straits Times, International Herald Tribune, Asian Wall Street Journal, and Financial Times). The evaluation was conducted in 2 stages: stage 1 involving abstracts produced manually by 2 human experts; stage 2 involving the generation of abstracts using NEWS_EXT. Results of each of the 4 approaches were compared with the human produced abstracts, where the title and location approaches were found to give the best results for both local and foreign news. Reports plans to refine and enhance NEWS_EXT and incorporate it as a module within a larger newspaper clipping system
    Source
    Asian libraries. 5(1996) no.1, S.34-42
  9. Salton, G.; Allan, J.; Buckley, C.; Singhal, A.: Automatic analysis, theme generation, and summarization of machine readable texts (1994) 0.00
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    Date
    16. 8.1998 12:30:29
  10. Craven, T.C.: ¬A phrase flipper for the assistance of writers of abstracts and other text (1995) 0.00
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    Date
    17. 8.1996 10:29:59
  11. 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
  12. Edmundson, H.P.; Wyllis, R.E.: Problems in automatic abstracting (1964) 0.00
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    Source
    Communications of the Association for Computing Machinery. 7(1964) no.1, S.259-263
  13. Mani, T.: Automatic summarization (2001) 0.00
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    Isbn
    1-58811-060-5
  14. 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.
  15. Johnson, F.C.: ¬A critical view of system-centered to user-centered evaluation of automatic abstracting research (1999) 0.00
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    Date
    1. 4.2002 13:48:19
  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. 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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  19. Oh, H.; Nam, S.; Zhu, Y.: Structured abstract summarization of scientific articles : summarization using full-text section information (2023) 0.00
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  20. Jiang, Y.; Meng, R.; Huang, Y.; Lu, W.; Liu, J.: Generating keyphrases for readers : a controllable keyphrase generation framework (2023) 0.00
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    Date
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Years

Types

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