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https://doi.org/10.1007/978-3-...
Part of book or chapter of book . 2023 . Peer-reviewed
License: Springer Nature TDM
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2022
License: CC BY
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An FPT Algorithm for Bipartite Vertex Splitting

Authors: Reyan Ahmed; Stephen Kobourov; Myroslav Kryven;

An FPT Algorithm for Bipartite Vertex Splitting

Abstract

Bipartite graphs model the relationship between two disjoint sets of objects. They have a wide range of applications and are often visualized as a 2-layered drawing, where each set of objects is visualized as a set of vertices (points) on one of the two parallel horizontal lines and the relationships are represented by edges (simple curves) between the two lines connecting the corresponding vertices. One of the common objectives in such drawings is to minimize the number of crossings this, however, is computationally expensive and may still result in drawings with so many crossings that they affect the readability of the drawing. We consider a recent approach to remove crossings in such visualizations by splitting vertices, where the goal is to find the minimum number of vertices to be split to obtain a planar drawing. We show that determining whether a planar drawing exists after splitting at most $k$ vertices is fixed parameter tractable in $k$.

Appears in the Proceedings of the 30th International Symposium on Graph Drawing and Network Visualization (GD 2022)

Keywords

Computational Geometry (cs.CG), FOS: Computer and information sciences, Discrete Mathematics (cs.DM), Computer Science - Computational Geometry, Computer Science - Discrete Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
Green