Search (46 results, page 1 of 3)

  • × theme_ss:"Retrievalalgorithmen"
  1. Rada, R.; Bicknell, E.: Ranking documents with a thesaurus (1989) 0.03 
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    Source
    Journal of the American Society for Information Science. 40(1989) no.5, S.304-310
  2. Niemi, T.; Junkkari, M.; Järvelin, K.; Viita, S.: Advanced query language for manipulating complex entities (2004) 0.02 
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    Information processing and management. 40(2004) no.6, S.869-
  3. Notess, G.R.: Search engine relevance : the never-ending quest (2000) 0.02 
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    Source
    Online. 24(2000) no.3, S.35-40
  4. Chung, Y.M.; Lee, J.Y.: Optimization of some factors affecting the performance of query expansion (2004) 0.02 
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    Source
    Information processing and management. 40(2004) no.6, S.891-
  5. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.02 
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  6. Silveira, M.; Ribeiro-Neto, B.: Concept-based ranking : a case study in the juridical domain (2004) 0.02 
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    Source
    Information processing and management. 40(2004) no.5, S.791-806
  7. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.02 
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    Date
    30. 3.2001 13:32:22
  8. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.02 
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    Date
    25. 8.2005 17:42:22
  9. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.02 
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    Date
    14. 6.2015 22:12:44
  10. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.02 
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    Date
    14. 6.2015 22:12:56
  11. Hora, M.: Methoden für das Ranking in Discovery-Systemen (2018) 0.01 
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    Date
    30. 5.2014 13:18:40
  12. MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004) 0.01 
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    Date
    20. 1.2007 18:30:22
  13. Faloutsos, C.: Signature files (1992) 0.01 
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    Date
    7. 5.1999 15:22:48
  14. Losada, D.E.; Barreiro, A.: Emebedding term similarity and inverse document frequency into a logical model of information retrieval (2003) 0.01 
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    Date
    22. 3.2003 19:27:23
  15. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.01 
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    Date
    22. 8.2014 17:05:18
  16. Tober, M.; Hennig, L.; Furch, D.: SEO Ranking-Faktoren und Rang-Korrelationen 2014 : Google Deutschland (2014) 0.01 
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    Date
    13. 9.2014 14:45:22
  17. Moffat, A.; Bell, T.A.H.: In situ generation of compressed inverted files (1995) 0.01 
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    Abstract
    An inverted index stores, for each term that appears in a collection of documents, a list of document numbers containing that term. Such an index is indispensible when Boolean or informal ranked queries are to be answered. Construction of the index ist, however, a non trivial task. Simple methods using in.memory data structures cannot be used for large collections because they require too much random access storage, and traditional disc based methods require large amounts of temporary file space. Describes a new indexing algorithm designed to create large compressed inverted indexes in situ. It makes use of simple compression codes for the positive integers and an in place external multi way merge sort. The new techniques has been used to invert a 2-gigabyte text collection in under 4 hours, using less than 40 megabytes of temporary disc space, and less than 20 megabytes of main memory
  18. Berry, M.W.; Browne, M.: Understanding search engines : mathematical modeling and text retrieval (1999) 0.01 
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    Date
    15.12.2006 14:49:40
  19. MacFarlane, A.; McCann, J.A.; Robertson, S.E.: Parallel methods for the generation of partitioned inverted files (2005) 0.01 
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    Date
    28. 1.2006 18:40:19
  20. Deerwester, S.; Dumais, S.; Landauer, T.; Furnass, G.; Beck, L.: Improving information retrieval with latent semantic indexing (1988) 0.01 
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    Pages
    S.36-40

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