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  • × theme_ss:"Data Mining"
  1. Lackes, R.; Tillmanns, C.: Data Mining für die Unternehmenspraxis : Entscheidungshilfen und Fallstudien mit führenden Softwarelösungen (2006) 0.03 
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    Content
    Modelle, Methoden und Werkzeuge: Ziele und Aufbau der Untersuchung.- Grundlagen.- Planung und Entscheidung mit Data-Mining-Unterstützung.- Methoden.- Funktionalität und Handling der Softwarelösungen. Fallstudien: Ausgangssituation und Datenbestand im Versandhandel.- Kundensegmentierung.- Erklärung regionaler Marketingerfolge zur Neukundengewinnung.Prognose des Customer Lifetime Values.- Selektion von Kunden für eine Direktmarketingaktion.- Welche Softwarelösung für welche Entscheidung?- Fazit und Marktentwicklungen.
    Date
    22. 3.2008 14:46:06
  2. Analytische Informationssysteme : Data Warehouse, On-Line Analytical Processing, Data Mining (1999) 0.02 
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    Content
    Grundlagen.- Data Warehouse.- On-line Analytical Processing.- Data Mining.- Betriebswirtschaftliche und strategische Aspekte.
  3. Drees, B.: Text und data mining : Herausforderungen und Möglichkeiten für Bibliotheken (2016) 0.01 
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    Content
    Vgl.: http://journals.ub.uni-heidelberg.de/index.php/bibliothek/article/view/33691/pdf.
    Source
    Perspektive Bibliothek. 5(2016) H.1, S.49-73
  4. Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997) 0.01 
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    Date
    5. 4.1996 15:29:15
    Source
    Information systems. 22(1997) nos.5/6, S.333-347
  5. Schwartz, D.: Graphische Datenanalyse für digitale Bibliotheken : Leistungs- und Funktionsumfang moderner Analyse- und Visualisierungsinstrumente (2006) 0.01 
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    Abstract
    Das World Wide Web stellt umfangreiche Datenmengen zur Verfügung. Für den Benutzer wird es zunehmend schwieriger, diese Datenmengen zu sichten, zu bewerten und die relevanten Daten herauszufiltern. Einen Lösungsansatz für diese Problemstellung bieten Visualisierungsinstrumente, mit deren Hilfe Rechercheergebnisse nicht mehr ausschließlich über textbasierte Dokumentenlisten, sondern über Symbole, Icons oder graphische Elemente dargestellt werden. Durch geeignete Visualisierungstechniken können Informationsstrukturen in großen Datenmengen aufgezeigt werden. Informationsvisualisierung ist damit ein Instrument, um Rechercheergebnisse in einer digitalen Bibliothek zu strukturieren und relevante Daten für den Benutzer leichter auffindbar zu machen.
  6. 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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    Date
    5. 4.1996 15:29:15
    Source
    Information systems. 22(1997) nos.5/6, S.349-385
  7. Budzik, J.; Hammond, K.J.; Birnbaum, L.: Information access in context (2001) 0.00 
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    Date
    29. 3.2002 17:31:17
  8. Chowdhury, G.G.: Template mining for information extraction from digital documents (1999) 0.00 
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    Date
    2. 4.2000 18:01:22
  9. Witten, I.H.; Frank, E.: Data Mining : Praktische Werkzeuge und Techniken für das maschinelle Lernen (2000) 0.00 
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    Date
    27. 1.1996 10:29:55
  10. Keim, D.A.: Data Mining mit bloßem Auge (2002) 0.00 
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    Date
    31.12.1996 19:29:41
  11. Kruse, R.; Borgelt, C.: Suche im Datendschungel (2002) 0.00 
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    Date
    31.12.1996 19:29:41
  12. Wrobel, S.: Lern- und Entdeckungsverfahren (2002) 0.00 
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    Date
    31.12.1996 19:29:41
  13. KDD : techniques and applications (1998) 0.00 
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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
  14. Borgelt, C.; Kruse, R.: Unsicheres Wissen nutzen (2002) 0.00 
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    Date
    31.12.1996 19:29:41
  15. Cardie, C.: Empirical methods in information extraction (1997) 0.00 
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    Date
    6. 3.1999 13:50:29
  16. Tiefschürfen in Datenbanken (2002) 0.00 
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    Date
    31.12.1996 19:29:41
  17. Bath, P.A.: Data mining in health and medical information (2003) 0.00 
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    Date
    23.10.2005 18:29:03
  18. Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997) 0.00 
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    Date
    22.11.1998 18:57:22
  19. Lusti, M.: Data Warehousing and Data Mining : Eine Einführung in entscheidungsunterstützende Systeme (1999) 0.00 
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    Date
    17. 7.2002 19:22:06
  20. Methodologies for knowledge discovery and data mining : Third Pacific-Asia Conference, PAKDD'99, Beijing, China, April 26-28, 1999, Proceedings (1999) 0.00 
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    Abstract
    The 29 revised full papers presented together with 37 short papers were carefully selected from a total of 158 submissions. The book is divided into sections on emerging KDD technology; association rules; feature selection and generation; mining in semi-unstructured data; interestingness, surprisingness, and exceptions; rough sets, fuzzy logic, and neural networks; induction, classification, and clustering; visualization, causal models and graph-based methods; agent-based and distributed data mining; and advanced topics and new methodologies

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  • e 20
  • d 17

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