Search (47 results, page 1 of 3)

  • × theme_ss:"Retrievalalgorithmen"
  1. Guerrero-Bote, V.P.; Moya Anegón, F. de; Herrero Solana, V.: Document organization using Kohonen's algorithm (2002) 0.09
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  2. Ravana, S.D.; Rajagopal, P.; Balakrishnan, V.: Ranking retrieval systems using pseudo relevance judgments (2015) 0.05
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    Date
    20. 1.2015 18:30:22
    18. 9.2018 18:22:56
  3. Yu, K.; Tresp, V.; Yu, S.: ¬A nonparametric hierarchical Bayesian framework for information filtering (2004) 0.04
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  4. Khoo, C.S.G.; Wan, K.-W.: ¬A simple relevancy-ranking strategy for an interface to Boolean OPACs (2004) 0.03
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    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."
    Source
    Electronic library. 22(2004) no.2, S.112-120
  5. Courtois, M.P.; Berry, M.W.: Results ranking in Web search engines (1999) 0.03
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    Abstract
    Comparaison des méthodes de classement de 5 moteurs de recherche (AltaVista, HotBot, Excie, Infoseek et Lycos). Sont testées la présence de tous les mots, la proximité et la localisation
  6. Campos, L.M. de; Fernández-Luna, J.M.; Huete, J.F.: Implementing relevance feedback in the Bayesian network retrieval model (2003) 0.03
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    Date
    22. 3.2003 19:30:19
  7. Torra, V.; Miyamoto, S.; Lanau, S.: Exploration of textual document archives using a fuzzy hierarchical clustering algorithm in the GAMBAL system (2005) 0.03
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  8. Figuerola, C.G.; Zazo, A.F.; Berrocal, J.L.A.: ¬La interaccion con el usuario en los sistemas de cuperacion de informacion realimentacion por relecvancia (2002) 0.03
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  9. Aigrain, P.; Longueville, V.: ¬A model for the evaluation of expansion techniques in information retrieval systems (1994) 0.02
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  10. Nagelschmidt, M.: Verfahren zur Anfragemodifikation im Information Retrieval (2008) 0.02
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    Pages
    V, 110 S. + CD
  11. Jindal, V.; Bawa, S.; Batra, S.: ¬A review of ranking approaches for semantic search on Web (2014) 0.02
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  12. Shah, B.; Raghavan, V.; Dhatric, P.; Zhao, X.: ¬A cluster-based approach for efficient content-based image retrieval using a similarity-preserving space transformation method (2006) 0.02
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  13. Lavrenko, V.: ¬A generative theory of relevance (2009) 0.02
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  14. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.02
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  15. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.01
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    Date
    30. 3.2001 13:32:22
  16. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.01
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    Date
    25. 8.2005 17:42:22
  17. Al-Hawamdeh, S.; Smith, G.; Willett, P.; Vere, R. de: Using nearest-neighbour searching techniques to access full-text documents (1991) 0.01
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  18. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.01
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    Date
    14. 6.2015 22:12:44
  19. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.01
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    Date
    14. 6.2015 22:12:56
  20. 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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