Context visualization for visual data mining

Mao Lin Huang; Quang Vinh Nguyen; Simeon J. Simoff; Michael H. Böhlen; Arturas Mazeika

Context visualization for visual data mining

Mao Lin Huang, Quang Vinh Nguyen, Simeon J. Simoff, Michael H. Böhlen, Arturas Mazeika

Research output: Chapter in Book / Conference Paper › Chapter

5 Citations (Scopus)

Abstract

Context and history visualization plays an important role in visual data mining especially in the visual exploration of large and complex data sets. The preservation of context and history information in the visualization can improve user comprehension of the exploration process as well as enhance the reusability of mining techniques and parameters to archive the desired results. This chapter presents methodology and various interactive visualization techniques supporting visual data mining in general as well as for visual preservation of context and history information. Algorithms are also described in supporting such methodology for visual data mining in real time.

Original language	English
Title of host publication	Visual Data Mining : Theory, Techniques and Tools for Visual Analytics
Place of Publication	Germany
Publisher	Springer
Pages	248-263
Number of pages	16
ISBN (Print)	9783540710790
Publication status	Published - 2008

Keywords

data mining
algorithms
information visualisation

Cite this

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title = "Context visualization for visual data mining",

abstract = "Context and history visualization plays an important role in visual data mining especially in the visual exploration of large and complex data sets. The preservation of context and history information in the visualization can improve user comprehension of the exploration process as well as enhance the reusability of mining techniques and parameters to archive the desired results. This chapter presents methodology and various interactive visualization techniques supporting visual data mining in general as well as for visual preservation of context and history information. Algorithms are also described in supporting such methodology for visual data mining in real time.",

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AU - Huang, Mao Lin

AU - Nguyen, Quang Vinh

AU - Simoff, Simeon J.

AU - Böhlen, Michael H.

AU - Mazeika, Arturas

PY - 2008

Y1 - 2008

N2 - Context and history visualization plays an important role in visual data mining especially in the visual exploration of large and complex data sets. The preservation of context and history information in the visualization can improve user comprehension of the exploration process as well as enhance the reusability of mining techniques and parameters to archive the desired results. This chapter presents methodology and various interactive visualization techniques supporting visual data mining in general as well as for visual preservation of context and history information. Algorithms are also described in supporting such methodology for visual data mining in real time.

AB - Context and history visualization plays an important role in visual data mining especially in the visual exploration of large and complex data sets. The preservation of context and history information in the visualization can improve user comprehension of the exploration process as well as enhance the reusability of mining techniques and parameters to archive the desired results. This chapter presents methodology and various interactive visualization techniques supporting visual data mining in general as well as for visual preservation of context and history information. Algorithms are also described in supporting such methodology for visual data mining in real time.

KW - data mining

KW - algorithms

KW - information visualisation

UR - http://handle.uws.edu.au:8081/1959.7/488868

M3 - Chapter

SN - 9783540710790

SP - 248

EP - 263

BT - Visual Data Mining : Theory, Techniques and Tools for Visual Analytics

PB - Springer

CY - Germany

ER -

Context visualization for visual data mining

Abstract

Keywords

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