Search (3 results, page 1 of 1)

  • × author_ss:"Savoy, J."
  • × theme_ss:"Retrievalstudien"
  1. Savoy, J.; Calvé, A. le; Vrajitoru, D.: Report on the TREC5 experiment : data fusion and collection fusion (1997) 0.00 
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    Type
    a
  2. Savoy, J.: Bibliographic database access using free-text and controlled vocabulary : an evaluation (2005) 0.00 
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    Abstract
    This paper evaluates and compares the retrieval effectiveness of various search models, based on either automatic text-word indexing or on manually assigned controlled descriptors. Retrieval is from a relatively large collection of bibliographic material written in French. Moreover, for this French collection we evaluate improvements that result from combining automatic and manual indexing. First, when considering various contexts, this study reveals that the combined indexing strategy always obtains the best retrieval performance. Second, when users wish to conduct exhaustive searches with minimal effort, we demonstrate that manually assigned terms are essential. Third, the evaluations presented in this paper study reveal the comparative retrieval performances that result from manual and automatic indexing in a variety of circumstances.
    Type
    a
  3. Abdou, S.; Savoy, J.: Searching in Medline : query expansion and manual indexing evaluation (2008) 0.00 
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    Abstract
    Based on a relatively large subset representing one third of the Medline collection, this paper evaluates ten different IR models, including recent developments in both probabilistic and language models. We show that the best performing IR models is a probabilistic model developed within the Divergence from Randomness framework [Amati, G., & van Rijsbergen, C.J. (2002) Probabilistic models of information retrieval based on measuring the divergence from randomness. ACM-Transactions on Information Systems 20(4), 357-389], which result in 170% enhancements in mean average precision when compared to the classical tf idf vector-space model. This paper also reports on our impact evaluations on the retrieval effectiveness of manually assigned descriptors (MeSH or Medical Subject Headings), showing that by including these terms retrieval performance can improve from 2.4% to 13.5%, depending on the underling IR model. Finally, we design a new general blind-query expansion approach showing improved retrieval performances compared to those obtained using the Rocchio approach.
    Type
    a

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