Search (20 results, page 1 of 1)

  • × year_i:[2000 TO 2010}
  • × theme_ss:"Retrievalalgorithmen"
  1. Liu, A.; Zou, Q.; Chu, W.W.: Configurable indexing and ranking for XML information retrieval (2004) 0.05 
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  2. Chen, Z.; Fu, B.: On the complexity of Rocchio's similarity-based relevance feedback algorithm (2007) 0.04 
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    Abstract
    Rocchio's similarity-based relevance feedback algorithm, one of the most important query reformation methods in information retrieval, is essentially an adaptive learning algorithm from examples in searching for documents represented by a linear classifier. Despite its popularity in various applications, there is little rigorous analysis of its learning complexity in literature. In this article, the authors prove for the first time that the learning complexity of Rocchio's algorithm is O(d + d**2(log d + log n)) over the discretized vector space {0, ... , n - 1 }**d when the inner product similarity measure is used. The upper bound on the learning complexity for searching for documents represented by a monotone linear classifier (q, 0) over {0, ... , n - 1 }d can be improved to, at most, 1 + 2k (n - 1) (log d + log(n - 1)), where k is the number of nonzero components in q. Several lower bounds on the learning complexity are also obtained for Rocchio's algorithm. For example, the authors prove that Rocchio's algorithm has a lower bound Omega((d über 2)log n) on its learning complexity over the Boolean vector space {0,1}**d.
  3. Sakai, T.: On the reliability of information retrieval metrics based on graded relevance (2007) 0.03 
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    Abstract
    This paper compares 14 information retrieval metrics based on graded relevance, together with 10 traditional metrics based on binary relevance, in terms of stability, sensitivity and resemblance of system rankings. More specifically, we compare these metrics using the Buckley/Voorhees stability method, the Voorhees/Buckley swap method and Kendall's rank correlation, with three data sets comprising test collections and submitted runs from NTCIR. Our experiments show that (Average) Normalised Discounted Cumulative Gain at document cut-off l are the best among the rank-based graded-relevance metrics, provided that l is large. On the other hand, if one requires a recall-based graded-relevance metric that is highly correlated with Average Precision, then Q-measure is the best choice. Moreover, these best graded-relevance metrics are at least as stable and sensitive as Average Precision, and are fairly robust to the choice of gain values.
  4. Crouch, C.J.; Crouch, D.B.; Chen, Q.; Holtz, S.J.: Improving the retrieval effectiveness of very short queries (2002) 0.03 
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  5. Wei, F.; Li, W.; Lu, Q.; He, Y.: Applying two-level reinforcement ranking in query-oriented multidocument summarization (2009) 0.03 
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  6. 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
  7. Hoenkamp, E.; Bruza, P.D.; Song, D.; Huang, Q.: ¬An effective approach to verbose queries using a limited dependencies language model (2009) 0.02 
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  8. 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
  9. 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
  10. Kanaeva, Z.: Ranking: Google und CiteSeer (2005) 0.01 
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    Date
    20. 3.2005 16:23:22
  11. 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
  12. 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
  13. 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
  14. Witschel, H.F.: Global term weights in distributed environments (2008) 0.01 
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    Date
    1. 8.2008 9:44:22
  15. 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
  16. 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
  17. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.01 
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    Date
    22. 3.2003 19:35:46
  18. 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
  19. Dominich, S.: Mathematical foundations of information retrieval (2001) 0.01 
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    Date
    22. 3.2008 12:26:32
  20. Khoo, C.S.G.; Wan, K.-W.: ¬A simple relevancy-ranking strategy for an interface to Boolean OPACs (2004) 0.01 
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    Source
    Electronic library. 22(2004) no.2, S.112-120

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  • e 19
  • d 1

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  • a 19
  • m 1

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