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Visual Data Mining: An Approach to Hybrid 3D Visualization
University of Borås, School of Business and IT.
2012 (English)Independent thesis Advanced level (degree of Master (One Year))Student thesis
Abstract [en]

By increasing the volume and complexity of datasets, Visual Data Mining (VDM), new visualization techniques evolved and new techniques released. However, some of these techniques performing well and cover all expectations; the others failed to save their positions. The main issue of such techniques is problem dependency. In this study, after a short description about necessity of Visual Data Mining techniques, I will provide a classified review of previous researches. This will result in a deep understanding as well as simple accessibility to previous researches, in a concise manner. This will facilitate the extraction of the specifications of 3D visualization technique and will provide a comprehensive knowledge of this technique in a classified manner. After that, all possible combination of 3D visualization technique will review. 3D Visualization technique as a popular technique is a concrete foundation for visualization of multi-dimensional datasets, but it has some limitations. To overcome these limitations, previous studies in literature as well as the experiences of professionals will gather. The results will prove the theoretical findings as well as offering new hybrid techniques (combination with 3D visualization and other visual data mining techniques). The contribution of professionals will empower and complement the results of this study, as they can address solutions for the weaknesses of 3D Visualization technique in their business which is new combination of techniques. These combinations of techniques will create the basis for future researches in order to discover new limitations and provide solutions to overcome by use of hybrid techniques.

Place, publisher, year, edition, pages
University of Borås/School of Business and IT , 2012.
Series
Magisteruppsats ; 2012MAGI02
Keywords [en]
Visual Data Mining, 3D-Graphs, Advantages, Disadvantages, Limitations, Hybrid techniques
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hb:diva-16601Local ID: 2320/11072OAI: oai:DiVA.org:hb-16601DiVA, id: diva2:1308489
Note
Program: Magisterutbildning i informatikAvailable from: 2019-04-30 Created: 2019-04-30

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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