Search (1 results, page 1 of 1)

  • × theme_ss:"Data Mining"
  • × theme_ss:"Retrievalalgorithmen"
  1. Biskri, I.; Rompré, L.: Using association rules for query reformulation (2012) 0.08
    0.0785128 = product of:
      0.1177692 = sum of:
        0.056935627 = weight(_text_:search in 92) [ClassicSimilarity], result of:
          0.056935627 = score(doc=92,freq=4.0), product of:
            0.1747324 = queryWeight, product of:
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.05027291 = queryNorm
            0.3258447 = fieldWeight in 92, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.046875 = fieldNorm(doc=92)
        0.060833566 = product of:
          0.12166713 = sum of:
            0.12166713 = weight(_text_:engines in 92) [ClassicSimilarity], result of:
              0.12166713 = score(doc=92,freq=4.0), product of:
                0.25542772 = queryWeight, product of:
                  5.080822 = idf(docFreq=746, maxDocs=44218)
                  0.05027291 = queryNorm
                0.47632706 = fieldWeight in 92, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  5.080822 = idf(docFreq=746, maxDocs=44218)
                  0.046875 = fieldNorm(doc=92)
          0.5 = coord(1/2)
      0.6666667 = coord(2/3)
    
    Footnote
    Vgl.: http://www.igi-global.com/book/next-generation-search-engines/64430.
    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a