Search (49 results, page 1 of 3)

  • × theme_ss:"Retrievalalgorithmen"
  • × year_i:[2000 TO 2010}
  1. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.06 
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    Date
    25.12.1995 19:20:34
    25. 8.2005 17:42:22
  2. MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004) 0.04 
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    Date
    12. 3.2001 11:34:20
    20. 1.2007 18:30:22
  3. Kanaeva, Z.: Ranking: Google und CiteSeer (2005) 0.03 
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    Date
    20. 3.2005 16:23:22
  4. 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
  5. Sparck Jones, K.: IDF term weighting and IR research lessons (2004) 0.01 
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    Date
    10. 3.1997 20:31:13
  6. Crestani, F.; Dominich, S.; Lalmas, M.; Rijsbergen, C.J.K. van: Mathematical, logical, and formal methods in information retrieval : an introduction to the special issue (2003) 0.01 
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    Date
    22. 3.2003 19:27:36
  7. Fan, W.; Fox, E.A.; Pathak, P.; Wu, H.: ¬The effects of fitness functions an genetic programming-based ranking discovery for Web search (2004) 0.01 
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    Date
    31. 5.2004 19:22:06
  8. Furner, J.: ¬A unifying model of document relatedness for hybrid search engines (2003) 0.01 
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    Date
    11. 9.2004 17:32:22
  9. Witschel, H.F.: Global term weights in distributed environments (2008) 0.01 
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    Date
    1. 8.2008 9:44:22
  10. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.01 
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    Date
    16.11.2008 16:22:48
  11. Campos, L.M. de; Fernández-Luna, J.M.; Huete, J.F.: Implementing relevance feedback in the Bayesian network retrieval model (2003) 0.01 
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    Date
    22. 3.2003 19:30:19
  12. Thelwall, M.; Vaughan, L.: New versions of PageRank employing alternative Web document models (2004) 0.01 
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    Date
    12. 3.2001 11:34:20
    20. 1.2007 18:32:28
  13. Kekäläinen, J.: Binary and graded relevance in IR evaluations : comparison of the effects on ranking of IR systems (2005) 0.01 
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    Abstract
    In this study the rankings of IR systems based on binary and graded relevance in TREC 7 and 8 data are compared. Relevance of a sample TREC results is reassessed using a relevance scale with four levels: non-relevant, marginally relevant, fairly relevant, highly relevant. Twenty-one topics and 90 systems from TREC 7 and 20 topics and 121 systems from TREC 8 form the data. Binary precision, and cumulated gain, discounted cumulated gain and normalised discounted cumulated gain are the measures compared. Different weighting schemes for relevance levels are tested with cumulated gain measures. Kendall's rank correlations are computed to determine to what extent the rankings produced by different measures are similar. Weighting schemes from binary to emphasising highly relevant documents form a continuum, where the measures correlate strongly in the binary end, and less in the heavily weighted end. The results show the different character of the measures.
    Date
    26.12.2007 20:29:18
  14. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.01 
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    Date
    22. 3.2003 19:35:46
  15. Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006) 0.01 
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    Date
    22. 7.2006 16:32:43
  16. Dominich, S.: Mathematical foundations of information retrieval (2001) 0.01 
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    Date
    22. 3.2008 12:26:32
  17. Kulyukin, V.A.; Settle, A.: Ranked retrieval with semantic networks and vector spaces (2001) 0.01 
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    Date
    16.12.2001 18:16:20
  18. López-Pujalte, C.; Guerrero-Bote, V.P.; Moya-Anegón, F. de: Order-based fitness functions for genetic algorithms applied to relevance feedback (2003) 0.01 
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    Abstract
    Lopez-Pujalte and Guerrero-Bote test a relevance feedback genetic algorithm while varying its order based fitness functions and generating a function based upon the Ide dec-hi method as a base line. Using the non-zero weighted term types assigned to the query, and to the initially retrieved set of documents, as genes, a chromosome of equal length is created for each. The algorithm is provided with the chromosomes for judged relevant documents, for judged irrelevant documents, and for the irrelevant documents with their terms negated. The algorithm uses random selection of all possible genes, but gives greater likelihood to those with higher fitness values. When the fittest chromosome of a previous population is eliminated it is restored while the least fittest of the new population is eliminated in its stead. A crossover probability of .8 and a mutation probability of .2 were used with 20 generations. Three fitness functions were utilized; the Horng and Yeh function which takes into account the position of relevant documents, and two new functions, one based on accumulating the cosine similarity for retrieved documents, the other on stored fixed-recall-interval precessions. The Cranfield collection was used with the first 15 documents retrieved from 33 queries chosen to have at least 3 relevant documents in the first 15 and at least 5 relevant documents not initially retrieved. Precision was calculated at fixed recall levels using the residual collection method which removes viewed documents. One of the three functions improved the original retrieval by127 percent, while the Ide dec-hi method provided a 120 percent improvement.
    Date
    5. 7.2006 19:28:20
  19. Weiß, B.: Verwandte Seiten finden : "Ähnliche Seiten" oder "What's Related" (2005) 0.01 
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    Date
    30.10.2005 20:14:41
    Pages
    20 S
  20. Losee, R.M.; Church Jr., L.: Are two document clusters better than one? : the cluster performance question for information retrieval (2005) 0.01 
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    Date
    20. 3.2005 11:16:14

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