3D visual data mining: goals and experiences

M Bohlen; L Bukauskas; PS Eriksen; SL Lauritzen; A Mazeika; P Musaeus; P Mylov

doi:10.1016/S0167-9473(02)00287-6

3D visual data mining: goals and experiences

M Bohlen, L Bukauskas, PS Eriksen, SL Lauritzen, A Mazeika, P Musaeus, P Mylov

11 Citations (Scopus)

Abstract

The visual exploration of large databases raises a number of unresolved inference problems and calls for new interaction patterns between multiple disciplines—both at the conceptual and technical level. We present an approach that is based on the interaction of four disciplines: database systems, statistical analyses, perceptual and cognitive psychology, and scientific visualization. At the conceptual level we offer perceptual and cognitive insights to guide the information visualization process. We then choose cluster surfaces to exemplify the data mining process, to discuss the tasks involved, and to work out the interaction patterns.

Original language	English
Journal	Computational Statistics & Data Analysis
Volume	43
Issue number	4
Pages (from-to)	445-469
Number of pages	25
ISSN	0167-9473
DOIs	https://doi.org/10.1016/S0167-9473(02)00287-6
Publication status	Published - 2003
Externally published	Yes

Access to Document

10.1016/S0167-9473(02)00287-6

Cite this

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AU - Mazeika, A

AU - Musaeus, P

AU - Mylov, P

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AB - The visual exploration of large databases raises a number of unresolved inference problems and calls for new interaction patterns between multiple disciplines—both at the conceptual and technical level. We present an approach that is based on the interaction of four disciplines: database systems, statistical analyses, perceptual and cognitive psychology, and scientific visualization. At the conceptual level we offer perceptual and cognitive insights to guide the information visualization process. We then choose cluster surfaces to exemplify the data mining process, to discuss the tasks involved, and to work out the interaction patterns.

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DO - 10.1016/S0167-9473(02)00287-6

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