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A conceptual framework for visual da...

Xia, Shan.

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A conceptual framework for visual data mining, with continuous semantic zooming.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	A conceptual framework for visual data mining, with continuous semantic zooming./
Author:	Xia, Shan.
Description:	162 p.
Notes:	Source: Dissertation Abstracts International, Volume: 71-02, Section: B, page: 1128.
Contained By:	Dissertation Abstracts International71-02B.
Subject:	Engineering, General. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3390798
ISBN:	9781109611090

A conceptual framework for visual data mining, with continuous semantic zooming.
Xia, Shan.

A conceptual framework for visual data mining, with continuous semantic zooming. - 162 p.

Source: Dissertation Abstracts International, Volume: 71-02, Section: B, page: 1128.

Thesis (Ph.D.)--The University of New Mexico, 2009.

With the growing pervasiveness of modern computer technology, sensors, and networks, the amount of data collected in and about society, medicine, and the environment, for example, is exploding. Large-scale data sets are typically complex making the interesting or novel information hidden within them hard to discover. Data mining algorithms and information visualization methodologies can help people explore these data sets by extracting knowledge and representing it in "meaningful" ways. The integration of data mining algorithms and information visualizations approaches is a growing field of research and application. In this research, we propose a conceptual framework to help in the understanding of unified data mining and information visualization systems. To explore this framework, we implement an archetypical hierarchical prototype that exposes the internal parameters of the framework allowing the quantitative evaluation of its usefulness. It is hypothesized that unified systems designed in the context of this conceptual framework will enhance human data exploration over traditional data mining systems. The result of a pilot study that uses an information visualization technique referred to as continuous semantic zooming in the visualization portion of the prototype is presented that begins to support this hypothesis. Moreover, this project conducts a larger scale human subject experiments to further assess this hypothesis, and empirically characterize the effects on human performance by unified systems designed in this manner. The main experiment study yields promising results and further supports the hypothesis.

ISBN: 9781109611090Subjects--Topical Terms:

1020744
Engineering, General.

A conceptual framework for visual data mining, with continuous semantic zooming.
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100 1 $a Xia, Shan. $3 1671197
245 1 2 $a A conceptual framework for visual data mining, with continuous semantic zooming.
300 $a 162 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-02, Section: B, page: 1128.
500 $a Adviser: Thomas P. Caudell.
502 $a Thesis (Ph.D.)--The University of New Mexico, 2009.
520 $a With the growing pervasiveness of modern computer technology, sensors, and networks, the amount of data collected in and about society, medicine, and the environment, for example, is exploding. Large-scale data sets are typically complex making the interesting or novel information hidden within them hard to discover. Data mining algorithms and information visualization methodologies can help people explore these data sets by extracting knowledge and representing it in "meaningful" ways. The integration of data mining algorithms and information visualizations approaches is a growing field of research and application. In this research, we propose a conceptual framework to help in the understanding of unified data mining and information visualization systems. To explore this framework, we implement an archetypical hierarchical prototype that exposes the internal parameters of the framework allowing the quantitative evaluation of its usefulness. It is hypothesized that unified systems designed in the context of this conceptual framework will enhance human data exploration over traditional data mining systems. The result of a pilot study that uses an information visualization technique referred to as continuous semantic zooming in the visualization portion of the prototype is presented that begins to support this hypothesis. Moreover, this project conducts a larger scale human subject experiments to further assess this hypothesis, and empirically characterize the effects on human performance by unified systems designed in this manner. The main experiment study yields promising results and further supports the hypothesis.
590 $a School code: 0142.
650 4 $a Engineering, General. $3 1020744
650 4 $a Computer Science. $3 626642
690 $a 0537
690 $a 0984
710 2 $a The University of New Mexico. $b Computer Engineering. $3 1670032
773 0 $t Dissertation Abstracts International $g 71-02B.
790 1 0 $a Caudell, Thomas P., $e advisor
790 1 0 $a Pattichis, Marios S. $e committee member
790 1 0 $a Sen, Pradeep $e committee member
790 1 0 $a Goldsmith, Timothy E. $e committee member
790 $a 0142
791 $a Ph.D.
792 $a 2009
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3390798