Search (7 results, page 1 of 1)

  • × theme_ss:"Retrievalalgorithmen"
  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × year_i:[1990 TO 2000}
  1. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.02 
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    Abstract
    Keyword based querying has been an immediate and efficient way to specify and retrieve related information that the user inquired. However, conventional document ranking based on an automatic assessment of document relevance to the query may not be the best approach when little information is given. Proposes an idea to integrate 2 existing techniques, query expansion and relevance feedback to achieve a concept-based information search for the Web
    Date
    1. 8.1996 22:08:06
  2. Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995) 0.01 
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    Date
    22. 2.1996 13:14:10
    Source
    Information processing and management. 31(1995) no.4, S.605-620
  3. Kwok, K.L.: ¬A network approach to probabilistic information retrieval (1995) 0.01 
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    Abstract
    Shows how probabilistic information retrieval based on document components may be implemented as a feedforward (feedbackward) artificial neural network. The network supports adaptation of connection weights as well as the growing of new edges between queries and terms based on user relevance feedback data for training, and it reflects query modification and expansion in information retrieval. A learning rule is applied that can also be viewed as supporting sequential learning using a harmonic sequence learning rate. Experimental results with 4 standard small collections and a large Wall Street Journal collection show that small query expansion levels of about 30 terms can achieve most of the gains at the low-recall high-precision region, while larger expansion levels continue to provide gains at the high-recall low-precision region of a precision recall curve
    Source
    ACM transactions on information systems. 13(1995) no.3, S.324-353
  4. Beaulieu, M.; Jones, S.: Interactive searching and interface issues in the Okapi best match probabilistic retrieval system (1998) 0.00 
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    Abstract
    Explores interface design raised by the development and evaluation of Okapi, a highly interactive information retrieval system based on a probabilistic retrieval model with relevance feedback. It uses terms frequency weighting functions to display retrieved items in a best match ranked order; it can also find additional items similar to those marked as relevant by the searcher. Compares the effectiveness of automatic and interactive query expansion in different user interface environments. focuses on the nature of interaction in information retrieval and the interrelationship between functional visibility, the user's cognitive loading and the balance of control between user and system
  5. Srinivasan, P.: Query expansion and MEDLINE (1996) 0.00 
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    Source
    Information processing and management. 32(1996) no.4, S.431-443
  6. Robertson, S.E.: OKAPI at TREC-3 (1995) 0.00 
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    Abstract
    Reports text information retrieval experiments performed as part of the 3 rd round of Text Retrieval Conferences (TREC) using the Okapi online catalogue system at City University, UK. The emphasis in TREC-3 was: further refinement of term weighting functions; an investigation of run time passage determination and searching; expansion of ad hoc queries by terms extracted from the top documents retrieved by a trial search; new methods for choosing query expansion terms after relevance feedback, now split into methods of ranking terms prior to selection and subsequent selection procedures; and the development of a user interface procedure within the new TREC interactive search framework
  7. Chen, H.; Zhang, Y.; Houston, A.L.: Semantic indexing and searching using a Hopfield net (1998) 0.00 
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    Source
    Journal of information science. 24(1998) no.1, S.3-18

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