Search (11 results, page 1 of 1)

  • × theme_ss:"Computerlinguistik"
  • × type_ss:"a"
  1. Frakes, W.B.: Stemming algorithms (1992) 5.78 
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  2. Abu-Salem, H.; Al-Omari, M.; Evens, M.W.: Stemming methodologies over individual query words for an Arabic information retrieval system (1999) 5.78 
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  3. French, J.C.; Powell, A.L.; Schulman, E.: Using clustering strategies for creating authority files (2000) 5.78 
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  4. Jones, K.: Linguistic searching versus relevance ranking : DR-LINK and TARGET (1999) 5.78 
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  5. Ponte, J.M.: Language models for relevance feedback (2000) 5.78 
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    Theme
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  6. 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) 5.78 
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  7. Herrera-Viedma, E.; Cordón, O.; Herrera, J.C.; Luqe, M.: ¬An IRS based on multi-granular lnguistic information (2003) 5.78 
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  8. Radev, D.; Fan, W.; Qu, H.; Wu, H.; Grewal, A.: Probabilistic question answering on the Web (2005) 5.78 
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  9. Symonds, M.; Bruza, P.; Zuccon, G.; Koopman, B.; Sitbon, L.; Turner, I.: Automatic query expansion : a structural linguistic perspective (2014) 5.78 
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  10. Hoenkamp, E.; Bruza, P.D.; Song, D.; Huang, Q.: ¬An effective approach to verbose queries using a limited dependencies language model (2009) 5.78 
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  11. Hoenkamp, E.; Bruza, P.: How everyday language can and will boost effective information retrieval (2015) 5.78 
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