Search (12 results, page 1 of 1)

  • × theme_ss:"Retrievalalgorithmen"
  • × theme_ss:"Computerlinguistik"
  1. Jones, K.: Linguistic searching versus relevance ranking : DR-LINK and TARGET (1999) 0.00
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    Source
    Online and CD-ROM review. 23(1999) no.2, S.67-80
  2. Herrera-Viedma, E.; Cordón, O.; Herrera, J.C.; Luqe, M.: ¬An IRS based on multi-granular lnguistic information (2003) 0.00
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    Abstract
    An information retrieval system (IRS) based on fuzzy multi-granular linguistic information is proposed. The system has an evaluation method to process multi-granular linguistic information, in such a way that the inputs to the IRS are represented in a different linguistic domain than the outputs. The system accepts Boolean queries whose terms are weighted by means of the ordinal linguistic values represented by the linguistic variable "Importance" assessed an a label set S. The system evaluates the weighted queries according to a threshold semantic and obtains the linguistic retrieval status values (RSV) of documents represented by a linguistic variable "Relevance" expressed in a different label set S'. The advantage of this linguistic IRS with respect to others is that the use of the multi-granular linguistic information facilitates and improves the IRS-user interaction
    Pages
    S.372-378
  3. Brenner, E.H.: Beyond Boolean : new approaches in information retrieval; the quest for intuitive online search systems past, present & future (1995) 0.00
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    Pages
    XV,143 S
    Type
    s
  4. Frakes, W.B.: Stemming algorithms (1992) 0.00
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    Pages
    S.131-160
  5. Hoenkamp, E.; Bruza, P.D.; Song, D.; Huang, Q.: ¬An effective approach to verbose queries using a limited dependencies language model (2009) 0.00
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    Footnote
    Vgl.: http://link.springer.com/chapter/10.1007%2F978-3-642-04417-5_11. Vgl. auch: http://eprints.qut.edu.au/47258/> (Accepted Version, 5 s.) / <http://eprints.qut.edu.au/29631/> (Conference Paper, 12 s.).
    Pages
    S.116-127
  6. French, J.C.; Powell, A.L.; Schulman, E.: Using clustering strategies for creating authority files (2000) 0.00
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    Source
    Journal of the American Society for Information Science. 51(2000) no.8, S.774-786
  7. Ponte, J.M.: Language models for relevance feedback (2000) 0.00
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    Pages
    S.73-95
  8. Beitzel, S.M.; Jensen, E.C.; Chowdhury, A.; Grossman, D.; Frieder, O; Goharian, N.: Fusion of effective retrieval strategies in the same information retrieval system (2004) 0.00
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    Source
    Journal of the American Society for Information Science and Technology. 55(2004) no.10, S.859-868
  9. 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
  10. Abu-Salem, H.; Al-Omari, M.; Evens, M.W.: Stemming methodologies over individual query words for an Arabic information retrieval system (1999) 0.00
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    Source
    Journal of the American Society for Information Science. 50(1999) no.6, S.524-529
  11. Symonds, M.; Bruza, P.; Zuccon, G.; Koopman, B.; Sitbon, L.; Turner, I.: Automatic query expansion : a structural linguistic perspective (2014) 0.00
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    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.8, S.1577-1596
  12. Hoenkamp, E.; Bruza, P.: How everyday language can and will boost effective information retrieval (2015) 0.00
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.8, S.1546-1558