Search (3 results, page 1 of 1)

  • × author_ss:"Efron, M."
  • × theme_ss:"Retrievalalgorithmen"
  1. Efron, M.; Winget, M.: Query polyrepresentation for ranking retrieval systems without relevance judgments (2010) 0.02 
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    Abstract
    Ranking information retrieval (IR) systems with respect to their effectiveness is a crucial operation during IR evaluation, as well as during data fusion. This article offers a novel method of approaching the system-ranking problem, based on the widely studied idea of polyrepresentation. The principle of polyrepresentation suggests that a single information need can be represented by many query articulations-what we call query aspects. By skimming the top k (where k is small) documents retrieved by a single system for multiple query aspects, we collect a set of documents that are likely to be relevant to a given test topic. Labeling these skimmed documents as putatively relevant lets us build pseudorelevance judgments without undue human intervention. We report experiments where using these pseudorelevance judgments delivers a rank ordering of IR systems that correlates highly with rankings based on human relevance judgments.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.6, S.1081-1091
  2. Efron, M.: Query expansion and dimensionality reduction : Notions of optimality in Rocchio relevance feedback and latent semantic indexing (2008) 0.00 
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    Source
    Information processing and management. 44(2008) no.1, S.163-180
  3. Efron, M.: Linear time series models for term weighting in information retrieval (2010) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.7, S.1299-1312

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