Search (8 results, page 1 of 1)

  • × theme_ss:"Data Mining"
  • × type_ss:"a"
  • × year_i:[1990 TO 2000}
  1. Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997) 0.02
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    Date
    22.11.1998 18:57:22
    Source
    Online. 21(1997) no.6, S.87-92
  2. Chowdhury, G.G.: Template mining for information extraction from digital documents (1999) 0.01
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    Date
    2. 4.2000 18:01:22
  3. Tunbridge, N.: Semiology put to data mining (1999) 0.01
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    Source
    Online and CD-ROM review. 23(1999) no.5, S.303-305
  4. Fayyad, U.M.; Djorgovski, S.G.; Weir, N.: From digitized images to online catalogs : data ming a sky server (1996) 0.01
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    Abstract
    Offers a data mining approach based on machine learning classification methods to the problem of automated cataloguing of online databases of digital images resulting from sky surveys. The SKICAT system automates the reduction and analysis of 3 terabytes of images expected to contain about 2 billion sky objects. It offers a solution to problems associated with the analysis of large data sets in science
  5. Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997) 0.01
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    Source
    Information systems. 22(1997) nos.5/6, S.333-347
  6. Saz, J.T.: Perspectivas en recuperacion y explotacion de informacion electronica : el 'data mining' (1997) 0.01
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    Footnote
    Übers. des Titels: Perspectives on the retrieval and exploitation of electronic information: data mining
  7. Hofstede, A.H.M. ter; Proper, H.A.; Van der Weide, T.P.: Exploiting fact verbalisation in conceptual information modelling (1997) 0.01
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    Source
    Information systems. 22(1997) nos.5/6, S.349-385
  8. Gaizauskas, R.; Wilks, Y.: Information extraction : beyond document retrieval (1998) 0.00
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    Abstract
    In this paper we give a synoptic view of the growth of the text processing technology of informatione xtraction (IE) whose function is to extract information about a pre-specified set of entities, relations or events from natural language texts and to record this information in structured representations called templates. Here we describe the nature of the IE task, review the history of the area from its origins in AI work in the 1960s and 70s till the present, discuss the techniques being used to carry out the task, describe application areas where IE systems are or are about to be at work, and conclude with a discussion of the challenges facing the area. What emerges is a picture of an exciting new text processing technology with a host of new applications, both on its own and in conjunction with other technologies, such as information retrieval, machine translation and data mining