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Visual Data Mining: Techniques and Tools for Data Visualization and MiningMay 2002
Publisher:
  • John Wiley & Sons, Inc.
  • 605 Third Ave. New York, NY
  • United States
ISBN:978-0-471-14999-6
Published:01 May 2002
Pages:
400
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Bibliometrics
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Abstract

From the Publisher:

Data mining techniques offer marketing analysts a better understanding of customer buying habits. That data can then be used to develop new marketing campaigns and new products. New visual mining tools are becoming widely available, and can provide a quick and easily accessible way of retrieving information. These visual techniques also have the ability to make it possible for nontechnical business managers to understand their markets and make more savvy business decisions.

Cited By

  1. Basole R, Huhtamäki J, Still K and Russell M (2016). Visual decision support for business ecosystem analysis, Expert Systems with Applications: An International Journal, 65:C, (271-282), Online publication date: 15-Dec-2016.
  2. Li D, Wang S, Yuan H and Li D (2016). Software and applications of spatial data mining, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 6:3, (84-114), Online publication date: 1-May-2016.
  3. ACM
    Bothorel G, Serrurier M and Hurter C From Visualization to Association Rules Proceedings of the 29th Spring Conference on Computer Graphics, (57-64)
  4. Borges Sampaio W, Moraes Diniz E, Corrêa Silva A, Cardoso de Paiva A and Gattass M (2011). Detection of masses in mammogram images using CNN, geostatistic functions and SVM, Computers in Biology and Medicine, 41:8, (653-664), Online publication date: 1-Aug-2011.
  5. George R, Nesbitt K, Gillard P and Donovan M Identifying cultural design requirements for an Australian indigenous website Proceedings of the Eleventh Australasian Conference on User Interface - Volume 106, (89-97)
  6. Yang C, Lin W, Chen H and Shi Y (2009). Improving scheduling of emergency physicians using data mining analysis, Expert Systems with Applications: An International Journal, 36:2, (3378-3387), Online publication date: 1-Mar-2009.
  7. Nesbitt K and Hoskens I Multi-sensory game interface improves player satisfaction but not performance Proceedings of the ninth conference on Australasian user interface - Volume 76, (13-18)
  8. ACM
    Assent I, Krieger R, Müller E and Seidl T (2007). VISA, ACM SIGKDD Explorations Newsletter, 9:2, (5-12), Online publication date: 1-Dec-2007.
  9. Kim S, Lele S, Ramalingam S and Fox E Visualizing user communities and usage trends of digital libraries based on user tracking information Proceedings of the 9th international conference on Asian Digital Libraries: achievements, Challenges and Opportunities, (111-120)
  10. Kabán A, Sun J, Raychaudhury S and Nolan L On class visualisation for high dimensional data Proceedings of the 9th international conference on Discovery Science, (125-136)
  11. Nesbitt K Modelling human perception to leverage the reuse of concepts across the multi-sensory design space Proceedings of the 3rd Asia-Pacific conference on Conceptual modelling - Volume 53, (65-74)
Contributors
  • University of California, Davis

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