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Robin, J.; McKeown, K.: Empirically designing and evaluating a new revision-based model for summary generation (1996) 0.03

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Date: 6. 3.1997 16:22:15

Automatic summarizing : introduction (1995) 0.02

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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

McKeown, K.; Robin, J.; Kukich, K.: Generating concise natural language summaries (1995) 0.01

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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.

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.

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.

Johnson, F.: Automatic abstracting research (1995) 0.01

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Harabagiu, S.; Hickl, A.; Lacatusu, F.: Satisfying information needs with multi-document summaries (2007) 0.01

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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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Moens, M.-F.: Summarizing court decisions (2007) 0.01

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Brandow, R.; Mitze, K.; Rau, L.F.: Automatic condensation of electronic publications by sentence selection (1995) 0.01

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Sparck Jones, K.; Endres-Niggemeyer, B.: Introduction: automatic summarizing (1995) 0.01

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Ahmad, K.: Text summarisation : the role of lexical cohesion analysis (1995) 0.01

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Gomez, J.; Allen, K.; Matney, M.; Awopetu, T.; Shafer, S.: Experimenting with a machine generated annotations pipeline (2020) 0.01

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Goh, A.; Hui, S.C.: TES: a text extraction system (1996) 0.01

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Date: 26. 2.1997 10:22:43

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

Moens, M.-F.; Uyttendaele, C.: Automatic text structuring and categorization as a first step in summarizing legal cases (1997) 0.01

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Moens, M.-F.; Uyttendaele, C.; Dumotier, J.: Abstracting of legal cases : the potential of clustering based on the selection of representative objects (1999) 0.01

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Liang, S.-F.; Devlin, S.; Tait, J.: Investigating sentence weighting components for automatic summarisation (2007) 0.01

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Martinez-Romo, J.; Araujo, L.; Fernandez, A.D.: SemGraph : extracting keyphrases following a novel semantic graph-based approach (2016) 0.01
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```
Abstract

Keyphrases represent the main topics a text is about. In this article, we introduce SemGraph, an unsupervised algorithm for extracting keyphrases from a collection of texts based on a semantic relationship graph. The main novelty of this algorithm is its ability to identify semantic relationships between words whose presence is statistically significant. Our method constructs a co-occurrence graph in which words appearing in the same document are linked, provided their presence in the collection is statistically significant with respect to a null model. Furthermore, the graph obtained is enriched with information from WordNet. We have used the most recent and standardized benchmark to evaluate the system ability to detect the keyphrases that are part of the text. The result is a method that achieves an improvement of 5.3% and 7.28% in F measure over the two labeled sets of keyphrases used in the evaluation of SemEval-2010.

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