Search (32 results, page 1 of 2)

  • × theme_ss:"Data Mining"
  1. Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997) 0.04 
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    Date
    22.11.1998 18:57:22
    Source
    Online. 21(1997) no.6, S.87-92
  2. Jäger, L.: Von Big Data zu Big Brother (2018) 0.02 
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    Date
    21. 1.2018 19:12:56
    22. 1.2018 11:33:49
  3. Chowdhury, G.G.: Template mining for information extraction from digital documents (1999) 0.02 
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    Date
    2. 4.2000 18:01:22
  4. KDD : techniques and applications (1998) 0.02 
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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. Mattison, R.: Data warehousing and data mining for telecommunications (1997) 0.02 
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    Footnote
    Rez. in: Database 21(1998) no.3, S.94 (J.D. Blackwell)
  6. Decker, B.: Data Mining in Öffentlichen Bibliotheken (2000) 0.02 
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    Date
    21. 5.2000 10:51:53
  7. Data Mining im praktischen Einsatz : Verfahren und Anwendungsfälle für Marketing, Vertrieb, Controlling und Kundenunterstützung (2000) 0.01 
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    Date
    26.11.2005 11:05:21
  8. Witten, I.H.; Frank, E.: Data Mining : Praktische Werkzeuge und Techniken für das maschinelle Lernen (2000) 0.01 
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    Date
    10.11.2001 21:27:08
  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. Information visualization in data mining and knowledge discovery (2002) 0.01 
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    Date
    23. 3.2008 19:10:22
    Footnote
    In 13 chapters, Part Two provides an introduction to KDD, an overview of data mining techniques, and examples of the usefulness of data model visualizations. The importance of visualization throughout the KDD process is stressed in many of the chapters. In particular, the need for measures of visualization effectiveness, benchmarking for identifying best practices, and the use of standardized sample data sets is convincingly presented. Many of the important data mining approaches are discussed in this complementary context. Cluster and outlier detection, classification techniques, and rule discovery algorithms are presented as the basic techniques common to the KDD process. The potential effectiveness of using visualization in the data modeling process are illustrated in chapters focused an using visualization for helping users understand the KDD process, ask questions and form hypotheses about their data, and evaluate the accuracy and veracity of their results. The 11 chapters of Part Three provide an overview of the KDD process and successful approaches to integrating KDD, data mining, and visualization in complementary domains. Rhodes (Chapter 21) begins this section with an excellent overview of the relation between the KDD process and data mining techniques. He states that the "primary goals of data mining are to describe the existing data and to predict the behavior or characteristics of future data of the same type" (p. 281). These goals are met by data mining tasks such as classification, regression, clustering, summarization, dependency modeling, and change or deviation detection. Subsequent chapters demonstrate how visualization can aid users in the interactive process of knowledge discovery by graphically representing the results from these iterative tasks. Finally, examples of the usefulness of integrating visualization and data mining tools in the domain of business, imagery and text mining, and massive data sets are provided. This text concludes with a thorough and useful 17-page index and lengthy yet integrating 17-page summary of the academic and industrial backgrounds of the contributing authors. A 16-page set of color inserts provide a better representation of the visualizations discussed, and a URL provided suggests that readers may view all the book's figures in color on-line, although as of this submission date it only provides access to a summary of the book and its contents. The overall contribution of this work is its focus an bridging two distinct areas of research, making it a valuable addition to the Morgan Kaufmann Series in Database Management Systems. The editors of this text have met their main goal of providing the first textbook integrating knowledge discovery, data mining, and visualization. Although it contributes greatly to our under- standing of the development and current state of the field, a major weakness of this text is that there is no concluding chapter to discuss the contributions of the sum of these contributed papers or give direction to possible future areas of research. "Integration of expertise between two different disciplines is a difficult process of communication and reeducation. Integrating data mining and visualization is particularly complex because each of these fields in itself must draw an a wide range of research experience" (p. 300). Although this work contributes to the crossdisciplinary communication needed to advance visualization in KDD, a more formal call for an interdisciplinary research agenda in a concluding chapter would have provided a more satisfying conclusion to a very good introductory text.
  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. Data mining : Theoretische Aspekte und Anwendungen (1998) 0.01 
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    Date
    21. 7.1999 16:44:40
  14. Lackes, R.; Tillmanns, C.: Data Mining für die Unternehmenspraxis : Entscheidungshilfen und Fallstudien mit führenden Softwarelösungen (2006) 0.01 
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    22. 3.2008 14:46:06
  15. Methodologies for knowledge discovery and data mining : Third Pacific-Asia Conference, PAKDD'99, Beijing, China, April 26-28, 1999, Proceedings (1999) 0.01 
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    Date
    21. 7.1999 17:09:12
  16. Baumgartner, R.: Methoden und Werkzeuge zur Webdatenextraktion (2006) 0.01 
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    Date
    3. 8.2006 21:16:35
  17. Hallonsten, O.; Holmberg, D.: Analyzing structural stratification in the Swedish higher education system : data contextualization with policy-history analysis (2013) 0.01 
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    Date
    22. 3.2013 19:43:01
  18. Vaughan, L.; Chen, Y.: Data mining from web search queries : a comparison of Google trends and Baidu index (2015) 0.01 
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    Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22
  19. Fonseca, F.; Marcinkowski, M.; Davis, C.: Cyber-human systems of thought and understanding (2019) 0.01 
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    Date
    7. 3.2019 16:32:22
  20. Li, J.; Zhang, P.; Cao, J.: External concept support for group support systems through Web mining (2009) 0.01 
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    18. 4.2009 20:59:21

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