Rodgers, Peter, Zhang, Leishi, Fish, Andrew (2008) General Euler Diagram Generation. In: 5th International Conference on Diagrammatic Representation and Inference, Herrsching, GERMANY. (doi:10.1007/978-3-540-87730-1_6) (KAR id:15622)
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Official URL: http://dx.doi.org/10.1007/978-3-540-87730-1_6 |
Abstract
Euler diagrams are a natural method of representing set-theoretic data and have been employed in diverse areas such as Visualizing statistical data, as a basis for diagrammatic logics and for displaying the results of database search queries. For effective use of Euler diagrams in practical computer based applications, the generation of a diagram as a set of curves from an abstract description is necessary. Various practical methods for Euler diagram generation have been proposed, but in all of these methods the diagrams that can be produced are only for it restricted Subset of all possible abstract descriptions. We describe a method for Euler diagram generation, demonstrated by implemented software. and illustrate the advances in methodology via the production of diagrams which were difficult or impossible to draw using previous approaches. To allow the generation of all abstract descriptions we may be reqUired to have some properties of the final diagram that are not considered nice. In particular we permit more than two curves to pass though it single point, permit sonic curve segments to be drawn Concurrently, and permit duplication of curve labels. However, Our method attempts to minimize these bad properties according to it chosen prioritization.
Item Type: | Conference or workshop item (Paper) |
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DOI/Identification number: | 10.1007/978-3-540-87730-1_6 |
Uncontrolled keywords: | euler diagrams; venn diagrams |
Subjects: | Q Science > QA Mathematics (inc Computing science) |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Depositing User: | Peter Rodgers |
Date Deposited: | 23 Feb 2010 12:33 UTC |
Last Modified: | 05 Nov 2024 09:50 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/15622 (The current URI for this page, for reference purposes) |
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