Search (55 results, page 1 of 3)

  • × theme_ss:"Data Mining"
  1. Schmid, J.: Data mining : wie finde ich in Datensammlungen entscheidungsrelevante Muster? (1999) 0.04
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    Source
    ARBIDO. 14(1999) H.5, S.11-13
  2. Peters, G.; Gaese, V.: ¬Das DocCat-System in der Textdokumentation von G+J (2003) 0.01
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    Date
    22. 4.2003 11:45:36
  3. 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
  4. KDD : techniques and applications (1998) 0.01
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    Footnote
    A special issue of selected papers from the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'97), held Singapore, 22-23 Feb 1997
  5. Budzik, J.; Hammond, K.J.; Birnbaum, L.: Information access in context (2001) 0.01
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  6. Medien-Informationsmanagement : Archivarische, dokumentarische, betriebswirtschaftliche, rechtliche und Berufsbild-Aspekte ; [Frühjahrstagung der Fachgruppe 7 im Jahr 2000 in Weimar und Folgetagung 2001 in Köln] (2003) 0.01
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    Content
    Enthält u.a. die Beiträge (Dokumentarische Aspekte): Günter Perers/Volker Gaese: Das DocCat-System in der Textdokumentation von Gr+J (Weimar 2000) Thomas Gerick: Finden statt suchen. Knowledge Retrieval in Wissensbanken. Mit organisiertem Wissen zu mehr Erfolg (Weimar 2000) Winfried Gödert: Aufbereitung und Rezeption von Information (Weimar 2000) Elisabeth Damen: Klassifikation als Ordnungssystem im elektronischen Pressearchiv (Köln 2001) Clemens Schlenkrich: Aspekte neuer Regelwerksarbeit - Multimediales Datenmodell für ARD und ZDF (Köln 2001) Josef Wandeler: Comprenez-vous only Bahnhof'? - Mehrsprachigkeit in der Mediendokumentation (Köln 200 1)
    Date
    11. 5.2008 19:49:22
  7. Data mining, data warehousing and client/server databases : Proceedings of the 8th International Hong Kong Computer Society Database Workshop (Academic Stream) (1997) 0.01
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    Editor
    Fong, J.
  8. Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997) 0.01
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    Date
    22.11.1998 18:57:22
  9. Lusti, M.: Data Warehousing and Data Mining : Eine Einführung in entscheidungsunterstützende Systeme (1999) 0.01
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    Date
    17. 7.2002 19:22:06
  10. 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
  11. Handbuch Web Mining im Marketing : Konzepte, Systeme, Fallstudien (2002) 0.01
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    Editor
    Hippner, H. et al.
  12. 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
  13. Li, J.; Zhang, P.; Cao, J.: External concept support for group support systems through Web mining (2009) 0.01
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  14. Ester, M.; Sander, J.: Knowledge discovery in databases : Techniken und Anwendungen (2000) 0.01
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  15. Witten, I.H.; Frank, E.: Data Mining : Praktische Werkzeuge und Techniken für das maschinelle Lernen (2000) 0.01
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    Footnote
    Rez. in: nfd 52(2001), H.7, S.427-428 (T. Mandl)
  16. Keim, D.A.: Data Mining mit bloßem Auge (2002) 0.01
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    Source
    Spektrum der Wissenschaft. 2002, H.11, S.88-91
  17. Kruse, R.; Borgelt, C.: Suche im Datendschungel (2002) 0.01
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    Source
    Spektrum der Wissenschaft. 2002, H.11, S.80-81
  18. Wrobel, S.: Lern- und Entdeckungsverfahren (2002) 0.01
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    Source
    Spektrum der Wissenschaft. 2002, H.11, S.85-87
  19. Lackes, R.; Tillmanns, C.: Data Mining für die Unternehmenspraxis : Entscheidungshilfen und Fallstudien mit führenden Softwarelösungen (2006) 0.01
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    Date
    22. 3.2008 14:46:06
  20. Hereth, J.; Stumme, G.; Wille, R.; Wille, U.: Conceptual knowledge discovery and data analysis (2000) 0.01
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    Abstract
    In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical theory which has been developed and proven useful during the last 20 years. Formal Concept Analysis has led to a theory of conceptual information systems which has been applied by using the management system TOSCANA in a wide range of domains. In this paper, we use such an application in database marketing to demonstrate how methods and procedures of CKDD can be applied in Data Analysis. In particular, we show the interplay and integration of data mining and data analysis techniques based on Formal Concept Analysis. The main concern of this paper is to explain how the transition from data to knowledge can be supported by a TOSCANA system. To clarify the transition steps we discuss their correspondence to the five levels of knowledge representation established by R. Brachman and to the steps of empirically grounded theory building proposed by A. Strauss and J. Corbin

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