Search (61 results, page 2 of 4)

  • × language_ss:"e"
  • × theme_ss:"Retrievalalgorithmen"
  1. 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
  2. Cheng, C.-S.; Chung, C.-P.; Shann, J.J.-J.: Fast query evaluation through document identifier assignment for inverted file-based information retrieval systems (2006) 0.01 
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  3. Carpineto, C.; Romano, G.: Information retrieval through hybrid navigation of lattice representations (1996) 0.01 
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  4. Boughanem, M.; Chrisment, C.; Tamine, L.: On using genetic algorithms for multimodal relevance optimization in information retrieval (2002) 0.01 
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  5. Lee, C.; Lee, G.G.: Probabilistic information retrieval model for a dependence structured indexing system (2005) 0.01 
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  6. López-Pujalte, C.; Guerrero-Bote, V.P.; Moya-Anegón, F. de: Genetic algorithms in relevance feedback : a second test and new contributions (2003) 0.01 
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  7. 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
  8. Kelledy, F.; Smeaton, A.F.: Signature files and beyond (1996) 0.01 
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    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  9. 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
  10. 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
  11. 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
  12. Witschel, H.F.: Global term weights in distributed environments (2008) 0.01 
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    Date
    1. 8.2008 9:44:22
  13. 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
  14. Ding, Y.; Chowdhury, G.; Foo, S.: Organsising keywords in a Web search environment : a methodology based on co-word analysis (2000) 0.01 
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    Source
    Dynamism and stability in knowledge organization: Proceedings of the 6th International ISKO-Conference, 10-13 July 2000, Toronto, Canada. Ed.: C. Beghtol et al
  15. Cecchini, R.L.; Lorenzetti, C.M.; Maguitman, A.G.; Brignole, N.B.: Multiobjective evolutionary algorithms for context-based search (2010) 0.01 
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    Abstract
    Formulating high-quality queries is a key aspect of context-based search. However, determining the effectiveness of a query is challenging because multiple objectives, such as high precision and high recall, are usually involved. In this work, we study techniques that can be applied to evolve contextualized queries when the criteria for determining query quality are based on multiple objectives. We report on the results of three different strategies for evolving queries: (a) single-objective, (b) multiobjective with Pareto-based ranking, and (c) multiobjective with aggregative ranking. After a comprehensive evaluation with a large set of topics, we discuss the limitations of the single-objective approach and observe that both the Pareto-based and aggregative strategies are highly effective for evolving topical queries. In particular, our experiments lead us to conclude that the multiobjective techniques are superior to a baseline as well as to well-known and ad hoc query reformulation techniques.
  16. Biskri, I.; Rompré, L.: Using association rules for query reformulation (2012) 0.01 
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    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  17. Habernal, I.; Konopík, M.; Rohlík, O.: Question answering (2012) 0.01 
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    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  18. Van der Veer Martens, B.; Fleet, C. van: Opening the black box of "relevance work" : a domain analysis (2012) 0.01 
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  19. Liu, J.; Liu, C.: Personalization in text information retrieval : a survey (2020) 0.01 
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  20. Burgin, R.: ¬The retrieval effectiveness of 5 clustering algorithms as a function of indexing exhaustivity (1995) 0.01 
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    Date
    22. 2.1996 11:20:06

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