Search (2 results, page 1 of 1)

0.0010484952 = product of:
  0.015727427 = sum of:
    0.015727427 = weight(_text_:und in 5542) [ClassicSimilarity], result of:
      0.015727427 = score(doc=5542,freq=2.0), product of:
        0.06422601 = queryWeight, product of:
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.028978055 = queryNorm
        0.24487628 = fieldWeight in 5542, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.216367 = idf(docFreq=13101, maxDocs=44218)
          0.078125 = fieldNorm(doc=5542)
  0.06666667 = coord(1/15)

Source

Sprachtechnologie für eine dynamische Wirtschaft im Medienzeitalter - Language technologies for dynamic business in the age of the media - L'ingénierie linguistique au service de la dynamisation économique à l'ère du multimédia: Tagungsakten der XXVI. Jahrestagung der Internationalen Vereinigung Sprache und Wirtschaft e.V., 23.-25.11.2000, Fachhochschule Köln. Hrsg.: K.-D. Schmitz

2.3255666E-4 = product of:
  0.0034883497 = sum of:
    0.0034883497 = product of:
      0.0069766995 = sum of:
        0.0069766995 = weight(_text_:information in 4245) [ClassicSimilarity], result of:
          0.0069766995 = score(doc=4245,freq=4.0), product of:
            0.050870337 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.028978055 = queryNorm
            0.13714671 = fieldWeight in 4245, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4245)
      0.5 = coord(1/2)
  0.06666667 = coord(1/15)

Abstract

Natural language generation (NLG), the automatic production of text by Computers, is commonly seen as a process consisting of the following distinct phases: Obviously, choosing words is a central aspect of generatiog language. In which of the these phases it should take place is not entirely clear, however. The decision depends an various factors: what exactly is seen as an individual lexical item; how the relation between word meaning and background knowledge (concepts) is defined; how one accounts for the interactions between individual lexical choices in the Same sentence; what criteria are employed for choosing between similar words; whether or not output is required in one or more languages. This article surveys these issues and the answers that have been proposed in NLG research. For many applications of natural language processing, large scale lexical resources have become available in recent years, such as the WordNet database. In language generation, however, generic lexicons are not in use yet; rather, almost every generation project develops its own format for lexical representations. The reason is that the entries of a generation lexicon need their specific interfaces to the Input representations processed by the generator; lexical semantics in an NLG lexicon needs to be tailored to the Input. Ort the other hand, the large lexicons used for language analysis typically have only very limited semantic information at all. Yet the syntactic behavior of words remains the same regardless of the particular application; thus, it should be possible to build at least parts of generic NLG lexical entries automatically, which could then be used by different systems.

Source

Encyclopedia of library and information science. Vol.70, [=Suppl.33]