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  • × author_ss:"Dumortier, J."
  1. Moens, M.F.; Dumortier, J.: Use of a text grammar for generating highlight abstracts of magazine articles (2000) 0.00 
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    Abstract
    Browsing a database of article abstracts is one way to select and buy relevant magazine articles online. Our research contributes to the design and development of text grammars for abstracting texts in unlimited subject domains. We developed a system that parses texts based on the text grammar of a specific text type and that extracts sentences and statements which are relevant for inclusion in the abstracts. The system employs knowledge of the discourse patterns that are typical of news stories. The results are encouraging and demonstrate the importance of discourse structures in text summarisation.
    Type
    a
  2. Moens, M.-F.; Dumortier, J.: Text categorization : the assignment of subject descriptors to magazine articles (2000) 0.00 
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    Type
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  3. Moens, M.-F.; Angheluta, R.; Dumortier, J.: Generic technologies for single-and multi-document summarization (2005) 0.00 
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    Abstract
    The technologies for single- and multi-document summarization that are described and evaluated in this article can be used on heterogeneous texts for different summarization tasks. They refer to the extraction of important sentences from the documents, compressing the sentences to their essential or relevant content, and detecting redundant content across sentences. The technologies are tested at the Document Understanding Conference, organized by the National Institute of Standards and Technology, USA in 2002 and 2003. The system obtained good to very good results in this competition. We tested our summarization system also on a variety of English Encyclopedia texts and on Dutch magazine articles. The results show that relying on generic linguistic resources and statistical techniques offer a basis for text summarization.
    Type
    a
  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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    Abstract
    The SALOMON project summarises Belgian criminal cases in order to improve access to the large number of existing and future cases. A double methodology was used when developing SALOMON: the cases are processed by employing additional knowledge to interpret structural patterns and features on the one hand and by way of occurrence statistics of index terms on the other. SALOMON performs an initial categorisation and structuring of the cases and subsequently extracts the most relevant text units of the alleged offences and of the opinion of the court. The SALOMON techniques do not themselves solve any legal questions, but they do guide the use effectively towards relevant texts
    Type
    a

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