3D visual data mining - Goals and experiences
Autor: | Peer Mylov, Steffen L. Lauritzen, Peter Musaeus, Linas Bukauskas, Michael H. Böhlen, Arturas Mažeika, Poul Svante Eriksen |
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Jazyk: | angličtina |
Rok vydání: | 2003 |
Předmět: |
Statistics and Probability
Observer relative data extraction Visual analytics business.industry Process (engineering) Computer science Applied Mathematics media_common.quotation_subject Scientific visualization Inference Cognition computer.software_genre Immersive data exploration Perception of space and objects Computational Mathematics Information visualization Data visualization Computational Theory and Mathematics Visual data mining Nested density surfaces Perception Data mining business computer media_common |
Zdroj: | Böhlen, M, Bukauskas, L, Svante Eriksen, P, Lilholt Lauritzen, S, Mažzeika, A, Musaeus, P & Mylov, P 2003, ' 3D visual data mining-Goals and experiences ', Computational Statistics and Data Analysis, vol. 43, no. 4, pp. 445-469 . https://doi.org/10.1016/S0167-9473(02)00287-6 |
DOI: | 10.1016/S0167-9473(02)00287-6 |
Popis: | 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. © 2003 Elsevier B.V. All rights reserved. |
Databáze: | OpenAIRE |
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