Search (143 results, page 1 of 8)

  • × theme_ss:"Retrievalalgorithmen"
  • × year_i:[2000 TO 2010}
  1. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.05 
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    Date
    25. 8.2005 17:42:22
    Language
    e
  2. MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004) 0.03 
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    Date
    20. 1.2007 18:30:22
    Language
    e
  3. Losada, D.E.; Barreiro, A.: Emebedding term similarity and inverse document frequency into a logical model of information retrieval (2003) 0.03 
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    Date
    22. 3.2003 19:27:23
    Language
    e
  4. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.02 
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    Date
    16.11.2008 16:22:48
    Language
    e
    Source
    Research and advanced technology for digital libraries : 8th European conference, ECDL 2004, Bath, UK, September 12-17, 2004 : proceedings. Eds.: Heery, R. u. E. Lyon
  5. 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) 0.02 
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    Date
    22. 3.2003 19:27:36
    Language
    e
  6. Fan, W.; Fox, E.A.; Pathak, P.; Wu, H.: ¬The effects of fitness functions an genetic programming-based ranking discovery for Web search (2004) 0.02 
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    Date
    31. 5.2004 19:22:06
    Language
    e
  7. Furner, J.: ¬A unifying model of document relatedness for hybrid search engines (2003) 0.02 
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    Date
    11. 9.2004 17:32:22
    Language
    e
  8. Witschel, H.F.: Global term weights in distributed environments (2008) 0.02 
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    Date
    1. 8.2008 9:44:22
    Language
    e
  9. Campos, L.M. de; Fernández-Luna, J.M.; Huete, J.F.: Implementing relevance feedback in the Bayesian network retrieval model (2003) 0.02 
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    Date
    22. 3.2003 19:30:19
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    e
  10. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.02 
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    Date
    22. 3.2003 19:35:46
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    e
  11. Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006) 0.02 
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    Date
    22. 7.2006 16:32:43
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    e
  12. Dominich, S.: Mathematical foundations of information retrieval (2001) 0.02 
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    Date
    22. 3.2008 12:26:32
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    e
  13. Khoo, C.S.G.; Wan, K.-W.: ¬A simple relevancy-ranking strategy for an interface to Boolean OPACs (2004) 0.02 
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    Abstract
    A relevancy-ranking algorithm for a natural language interface to Boolean online public access catalogs (OPACs) was formulated and compared with that currently used in a knowledge-based search interface called the E-Referencer, being developed by the authors. The algorithm makes use of seven weIl-known ranking criteria: breadth of match, section weighting, proximity of query words, variant word forms (stemming), document frequency, term frequency and document length. The algorithm converts a natural language query into a series of increasingly broader Boolean search statements. In a small experiment with ten subjects in which the algorithm was simulated by hand, the algorithm obtained good results with a mean overall precision of 0.42 and mean average precision of 0.62, representing a 27 percent improvement in precision and 41 percent improvement in average precision compared to the E-Referencer. The usefulness of each step in the algorithm was analyzed and suggestions are made for improving the algorithm.
    Content
    "Most Web search engines accept natural language queries, perform some kind of fuzzy matching and produce ranked output, displaying first the documents that are most likely to be relevant. On the other hand, most library online public access catalogs (OPACs) an the Web are still Boolean retrieval systems that perform exact matching, and require users to express their search requests precisely in a Boolean search language and to refine their search statements to improve the search results. It is well-documented that users have difficulty searching Boolean OPACs effectively (e.g. Borgman, 1996; Ensor, 1992; Wallace, 1993). One approach to making OPACs easier to use is to develop a natural language search interface that acts as a middleware between the user's Web browser and the OPAC system. The search interface can accept a natural language query from the user and reformulate it as a series of Boolean search statements that are then submitted to the OPAC. The records retrieved by the OPAC are ranked by the search interface before forwarding them to the user's Web browser. The user, then, does not need to interact directly with the Boolean OPAC but with the natural language search interface or search intermediary. The search interface interacts with the OPAC system an the user's behalf. The advantage of this approach is that no modification to the OPAC or library system is required. Furthermore, the search interface can access multiple OPACs, acting as a meta search engine, and integrate search results from various OPACs before sending them to the user. The search interface needs to incorporate a method for converting the user's natural language query into a series of Boolean search statements, and for ranking the OPAC records retrieved. The purpose of this study was to develop a relevancyranking algorithm for a search interface to Boolean OPAC systems. This is part of an on-going effort to develop a knowledge-based search interface to OPACs called the E-Referencer (Khoo et al., 1998, 1999; Poo et al., 2000). E-Referencer v. 2 that has been implemented applies a repertoire of initial search strategies and reformulation strategies to retrieve records from OPACs using the Z39.50 protocol, and also assists users in mapping query keywords to the Library of Congress subject headings."
    Language
    e
    Object
    E-Referencer
    Source
    Electronic library. 22(2004) no.2, S.112-120
  14. Kanaeva, Z.: Ranking: Google und CiteSeer (2005) 0.01 
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    Date
    20. 3.2005 16:23:22
  15. Wechsler, M.; Schäuble, P.: ¬The probability ranking principle revisited (2000) 0.00 
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  16. Liddy, E.D.; Diamond, T.; McKenna, M.: DR-LINK in TIPSTER (2000) 0.00 
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  17. Daniowicz, C.; Baliski, J.: Document ranking based upon Markov chains (2001) 0.00 
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  18. Horng, J.T.; Yeh, C.C.: Applying genetic algorithms to query optimization in document retrieval (2000) 0.00 
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  19. Zhang, D.; Dong, Y.: ¬An effective algorithm to rank Web resources (2000) 0.00 
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