Search (10 results, page 1 of 1)

  • × theme_ss:"Sprachretrieval"
  • × type_ss:"a"
  • × year_i:[2000 TO 2010}
  1. Voorhees, E.M.: Question answering in TREC (2005) 0.01 
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  2. Lin, J.; Katz, B.: Building a reusable test collection for question answering (2006) 0.01 
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    Abstract
    In contrast to traditional information retrieval systems, which return ranked lists of documents that users must manually browse through, a question answering system attempts to directly answer natural language questions posed by the user. Although such systems possess language-processing capabilities, they still rely on traditional document retrieval techniques to generate an initial candidate set of documents. In this article, the authors argue that document retrieval for question answering represents a task different from retrieving documents in response to more general retrospective information needs. Thus, to guide future system development, specialized question answering test collections must be constructed. They show that the current evaluation resources have major shortcomings; to remedy the situation, they have manually created a small, reusable question answering test collection for research purposes. In this article they describe their methodology for building this test collection and discuss issues they encountered regarding the notion of "answer correctness."
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.7, S.851-861
  3. Tartakovski, O.; Shramko, M.: Implementierung eines Werkzeugs zur Sprachidentifikation in mono- und multilingualen Texten (2006) 0.01 
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    Abstract
    Die Identifikation der Sprache bzw. der Sprachen in Textdokumenten ist einer der wichtigsten Schritte maschineller Textverarbeitung für das Information Retrieval. Der vorliegende Artikel stellt Langldent vor, ein System zur Sprachidentifikation von mono- und multilingualen elektronischen Textdokumenten. Das System bietet sowohl eine Auswahl von gängigen Algorithmen für die Sprachidentifikation monolingualer Textdokumente als auch einen neuen Algorithmus für die Sprachidentifikation multilingualer Textdokumente.
    Source
    Effektive Information Retrieval Verfahren in Theorie und Praxis: ausgewählte und erweiterte Beiträge des Vierten Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2005), Hildesheim, 20.7.2005. Hrsg.: T. Mandl u. C. Womser-Hacker
  4. Nhongkai, S.N.; Bentz, H.-J.: Bilinguale Suche mittels Konzeptnetzen (2006) 0.00 
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    Source
    Effektive Information Retrieval Verfahren in Theorie und Praxis: ausgewählte und erweiterte Beiträge des Vierten Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2005), Hildesheim, 20.7.2005. Hrsg.: T. Mandl u. C. Womser-Hacker
  5. Pomerantz, J.: ¬A linguistic analysis of question taxonomies (2005) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.7, S.715-728
  6. Ferret, O.; Grau, B.; Hurault-Plantet, M.; Illouz, G.; Jacquemin, C.; Monceaux, L.; Robba, I.; Vilnat, A.: How NLP can improve question answering (2002) 0.00 
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    Abstract
    Answering open-domain factual questions requires Natural Language processing for refining document selection and answer identification. With our system QALC, we have participated in the Question Answering track of the TREC8, TREC9 and TREC10 evaluations. QALC performs an analysis of documents relying an multiword term searches and their linguistic variation both to minimize the number of documents selected and to provide additional clues when comparing question and sentence representations. This comparison process also makes use of the results of a syntactic parsing of the questions and Named Entity recognition functionalities. Answer extraction relies an the application of syntactic patterns chosen according to the kind of information that is sought, and categorized depending an the syntactic form of the question. These patterns allow QALC to handle nicely linguistic variations at the answer level.
  7. Radev, D.; Fan, W.; Qu, H.; Wu, H.; Grewal, A.: Probabilistic question answering on the Web (2005) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.6, S.571-583
  8. Jensen, N.: Evaluierung von mehrsprachigem Web-Retrieval : Experimente mit dem EuroGOV-Korpus im Rahmen des Cross Language Evaluation Forum (CLEF) (2006) 0.00 
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    Source
    Effektive Information Retrieval Verfahren in Theorie und Praxis: ausgewählte und erweiterte Beiträge des Vierten Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2005), Hildesheim, 20.7.2005. Hrsg.: T. Mandl u. C. Womser-Hacker
  9. Strötgen, R.; Mandl, T.; Schneider, R.: Entwicklung und Evaluierung eines Question Answering Systems im Rahmen des Cross Language Evaluation Forum (CLEF) (2006) 0.00 
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    Source
    Effektive Information Retrieval Verfahren in Theorie und Praxis: ausgewählte und erweiterte Beiträge des Vierten Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2005), Hildesheim, 20.7.2005. Hrsg.: T. Mandl u. C. Womser-Hacker
  10. Kruschwitz, U.; AI-Bakour, H.: Users want more sophisticated search assistants : results of a task-based evaluation (2005) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.13, S.1377-1393

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