Search (2 results, page 1 of 1)

  • × author_ss:"Song, D."
  • × theme_ss:"Retrievalalgorithmen"
  1. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.01 
    0.010578786 = product of:
  0.049367666 = sum of:
    0.016731806 = weight(_text_:information in 1428) [ClassicSimilarity], result of:
      0.016731806 = score(doc=1428,freq=22.0), product of:
        0.052020688 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.029633347 = queryNorm
        0.32163754 = fieldWeight in 1428, product of:
          4.690416 = tf(freq=22.0), with freq of:
            22.0 = termFreq=22.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1428)
    0.025944345 = weight(_text_:retrieval in 1428) [ClassicSimilarity], result of:
      0.025944345 = score(doc=1428,freq=6.0), product of:
        0.08963835 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.029633347 = queryNorm
        0.28943354 = fieldWeight in 1428, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1428)
    0.0066915164 = product of:
      0.020074548 = sum of:
        0.020074548 = weight(_text_:22 in 1428) [ClassicSimilarity], result of:
          0.020074548 = score(doc=1428,freq=2.0), product of:
            0.103770934 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.029633347 = queryNorm
            0.19345059 = fieldWeight in 1428, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1428)
      0.33333334 = coord(1/3)
  0.21428572 = coord(3/14)
    Abstract
    Humans can make hasty, but generally robust judgements about what a text fragment is, or is not, about. Such judgements are termed information inference. This article furnishes an account of information inference from a psychologistic stance. By drawing an theories from nonclassical logic and applied cognition, an information inference mechanism is proposed that makes inferences via computations of information flow through an approximation of a conceptual space. Within a conceptual space information is represented geometrically. In this article, geometric representations of words are realized as vectors in a high dimensional semantic space, which is automatically constructed from a text corpus. Two approaches were presented for priming vector representations according to context. The first approach uses a concept combination heuristic to adjust the vector representation of a concept in the light of the representation of another concept. The second approach computes a prototypical concept an the basis of exemplar trace texts and moves it in the dimensional space according to the context. Information inference is evaluated by measuring the effectiveness of query models derived by information flow computations. Results show that information flow contributes significantly to query model effectiveness, particularly with respect to precision. Moreover, retrieval effectiveness compares favorably with two probabilistic query models, and another based an semantic association. More generally, this article can be seen as a contribution towards realizing operational systems that mimic text-based human reasoning.
    Date
    22. 3.2003 19:35:46
    Footnote
    Beitrag eines Themenheftes: Mathematical, logical, and formal methods in information retrieval
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.4, S.321-334
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  2. Hoenkamp, E.; Bruza, P.D.; Song, D.; Huang, Q.: ¬An effective approach to verbose queries using a limited dependencies language model (2009) 0.00 
    0.0032363355 = product of:
  0.022654347 = sum of:
    0.005707573 = weight(_text_:information in 2122) [ClassicSimilarity], result of:
      0.005707573 = score(doc=2122,freq=4.0), product of:
        0.052020688 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.029633347 = queryNorm
        0.10971737 = fieldWeight in 2122, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.03125 = fieldNorm(doc=2122)
    0.016946774 = weight(_text_:retrieval in 2122) [ClassicSimilarity], result of:
      0.016946774 = score(doc=2122,freq=4.0), product of:
        0.08963835 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.029633347 = queryNorm
        0.18905719 = fieldWeight in 2122, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.03125 = fieldNorm(doc=2122)
  0.14285715 = coord(2/14)
    Series
    Lecture notes in computer science : advances in information retrieval theory; 5766
    Source
    Second International Conference on the Theory of Information Retrieval, ICTIR 2009 Cambridge, UK, September 10-12, 2009 Proceedings. Ed.: L. Azzopardi

Authors

Themes