Search (41 results, page 1 of 3)

  • × theme_ss:"Retrievalalgorithmen"
  1. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.05
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    Date
    1. 8.1996 22:08:06
    Footnote
    Contribution to a special issue devoted to the Proceedings of the 7th International World Wide Web Conference, held 14-18 April 1998, Brisbane, Australia
  2. Furner, J.: ¬A unifying model of document relatedness for hybrid search engines (2003) 0.04
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    Date
    11. 9.2004 17:32:22
    Source
    Challenges in knowledge representation and organization for the 21st century: Integration of knowledge across boundaries. Proceedings of the 7th ISKO International Conference Granada, Spain, July 10-13, 2002. Ed.: M. López-Huertas
  3. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.03
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  4. 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
  5. 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
  6. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.02
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    Date
    14. 6.2015 22:12:44
  7. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.02
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    Date
    14. 6.2015 22:12:56
  8. Ruthven, I.; Lalmas, M.: Selective relevance feedback using term characteristics (1999) 0.02
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    Source
    Vocabulary as a central concept in digital libraries: interdisciplinary concepts, challenges, and opportunities : proceedings of the Third International Conference an Conceptions of Library and Information Science (COLIS3), Dubrovnik, Croatia, 23-26 May 1999. Ed. by T. Arpanac et al
  9. Liu, A.; Zou, Q.; Chu, W.W.: Configurable indexing and ranking for XML information retrieval (2004) 0.02
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    Source
    SIGIR'04: Proceedings of the 27th Annual International ACM-SIGIR Conference an Research and Development in Information Retrieval. Ed.: K. Järvelin, u.a
  10. Yu, K.; Tresp, V.; Yu, S.: ¬A nonparametric hierarchical Bayesian framework for information filtering (2004) 0.02
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    Source
    SIGIR'04: Proceedings of the 27th Annual International ACM-SIGIR Conference an Research and Development in Information Retrieval. Ed.: K. Järvelin, u.a
  11. 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
  12. Faloutsos, C.: Signature files (1992) 0.01
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    Date
    7. 5.1999 15:22:48
  13. 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
  14. 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
  15. 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
  16. Ravana, S.D.; Rajagopal, P.; Balakrishnan, V.: Ranking retrieval systems using pseudo relevance judgments (2015) 0.01
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    Date
    20. 1.2015 18:30:22
    18. 9.2018 18:22:56
  17. Kanaeva, Z.: Ranking: Google und CiteSeer (2005) 0.01
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    Date
    20. 3.2005 16:23:22
  18. Couvreur, T.R.; Benzel, R.N.; Miller, S.F.; Zeitler, D.N.; Lee, D.L.; Singhal, M.; Shivaratri, N.; Wong, W.Y.P.: ¬An analysis of performance and cost factors in searching large text databases using parallel search systems (1994) 0.01
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    Abstract
    The results of modelling the performance of searching large text databases (>10 GBytes) via various parallel hardware architectures and search algorithms are discussed. The performance under load and the cost of each configuration are compared. Strengths, weaknesses, performance sensitivities, and search features supported for each configuration are also addressed. In addition, a common search workload used in the modelling is described. The search workload is derived from a set of searches run against the Chemical Abstracts file of bibliographic and abstract text available on STN International. This common workload is applied to all configurations modelled to provide a common basis of comparison
  19. Carpineto, C.; Romano, G.: Information retrieval through hybrid navigation of lattice representations (1996) 0.01
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    Source
    International journal of human-computer studies. 45(1996) no.5, S.553-578
  20. Joss, M.W.; Wszola, S.: ¬The engines that can : text search and retrieval software, their strategies, and vendors (1996) 0.01
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    Date
    12. 9.1996 13:56:22

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