Search (2 results, page 1 of 1)

  • × theme_ss:"Retrievalalgorithmen"
  • × author_ss:"Stock, W.G."
  1. Weller, K.; Stock, W.G.: Transitive meronymy : automatic concept-based query expansion using weighted transitive part-whole relations (2008) 0.00
    0.0010357393 = product of:
      0.007250175 = sum of:
        0.007250175 = product of:
          0.036250874 = sum of:
            0.036250874 = weight(_text_:retrieval in 1835) [ClassicSimilarity], result of:
              0.036250874 = score(doc=1835,freq=4.0), product of:
                0.109568894 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03622214 = queryNorm
                0.33085006 = fieldWeight in 1835, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=1835)
          0.2 = coord(1/5)
      0.14285715 = coord(1/7)
    
    Abstract
    Transitive Meronymie. Automatische begriffsbasierte Suchanfrageerweiterung unter Nutzung gewichteter transitiver Teil-Ganzes-Relationen. Unsere theoretisch orientierte Arbeit isoliert transitive Teil-Ganzes-Beziehungen. Wir diskutieren den Einsatz der Meronymie bei der automatischen begriffsbasierten Suchanfrageerweiterung im Information Retrieval. Aus praktischen Gründen schlagen wir vor, die Bestandsrelationen zu spezifizieren und die einzelnen Arten mit unterschiedlichen Gewichtungswerten zu versehen, die im Retrieval genutzt werden. Für das Design von Wissensordnungen ist bedeutsam, dass innerhalb der Begriffsleiter einer Abstraktionsrelation ein Begriff alle seine Teile (sowie alle transitiven Teile der Teile) an seine Unterbegriffe vererbt.
  2. Stock, W.G.: On relevance distributions (2006) 0.00
    8.3700387E-4 = product of:
      0.0058590267 = sum of:
        0.0058590267 = product of:
          0.029295133 = sum of:
            0.029295133 = weight(_text_:retrieval in 5116) [ClassicSimilarity], result of:
              0.029295133 = score(doc=5116,freq=2.0), product of:
                0.109568894 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03622214 = queryNorm
                0.26736724 = fieldWeight in 5116, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.0625 = fieldNorm(doc=5116)
          0.2 = coord(1/5)
      0.14285715 = coord(1/7)
    
    Abstract
    There are at least three possible ways that documents are distributed by relevance: informetric (power law), inverse logistic, and dichotomous. The nature of the type of distribution has implications for the construction of relevance ranking algorithms for search engines, for automated (blind) relevance feedback, for user behavior when using Web search engines, for combining of outputs of search engines for metasearch, for topic detection and tracking, and for the methodology of evaluation of information retrieval systems.