Search (1 results, page 1 of 1)

  • × author_ss:"Burke, R.D."
  • × theme_ss:"Sprachretrieval"
  • × type_ss:"a"
  1. Burke, R.D.: Question answering from frequently asked question files : experiences with the FAQ Finder System (1997) 0.00
    0.0042405236 = product of:
      0.029683663 = sum of:
        0.029683663 = product of:
          0.07420915 = sum of:
            0.029295133 = weight(_text_:retrieval in 1191) [ClassicSimilarity], result of:
              0.029295133 = score(doc=1191,freq=2.0), product of:
                0.109568894 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.03622214 = queryNorm
                0.26736724 = fieldWeight in 1191, 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=1191)
            0.044914022 = weight(_text_:system in 1191) [ClassicSimilarity], result of:
              0.044914022 = score(doc=1191,freq=4.0), product of:
                0.11408355 = queryWeight, product of:
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.03622214 = queryNorm
                0.3936941 = fieldWeight in 1191, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.0625 = fieldNorm(doc=1191)
          0.4 = coord(2/5)
      0.14285715 = coord(1/7)
    
    Abstract
    Describes FAQ Finder, a natural language question-answering system that uses files of frequently asked questions as its knowledge base. Unlike information retrieval approaches that rely on a purely lexical metric of similarity between query and document, FAQ Finder uses a semantic knowledge base (Wordnet) to improve its ability to match question and answer. Includes results from an evaluation of the system's performance and shows that a combination of semantic and statistical techniques works better than any single approach