Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/90506
Title: Are crossings important for drawing large graphs?
Authors: Kobourov, S. G.
Pupyrev, S.
Saket, B.
Issue Date: 2014
Publisher: Springer Verlag
Citation: Kobourov, S. G. Are crossings important for drawing large graphs? / S. G. Kobourov, S. Pupyrev, B. Saket. — DOI 10.1007/978-3-662-45803-7_20 // Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). — 2014. — Iss. 8871. — P. 234-245.
Abstract: Reducing the number of edge crossings is considered one of the most important graph drawing aesthetics. While real-world graphs tend to be large and dense, most of the earlier work on evaluating the impact of edge crossings utilizes relatively small graphs that are manually generated and manipulated. We study the effect on task performance of increased edge crossings in automatically generated layouts for graphs, from different datasets, with different sizes, and with different densities. The results indicate that increasing the number of crossings negatively impacts accuracy and performance time and that impact is significant for small graphs but not significant for large graphs. We also quantitatively evaluate the impact of edge crossings on crossing angles and stress in automatically constructed graph layouts. We find a moderate correlation between minimizing stress and the minimizing the number of crossings. © Springer-Verlag Berlin Heidelberg 2014.
Keywords: ARTIFICIAL INTELLIGENCE
COMPUTER SCIENCE
COMPUTERS
AUTOMATICALLY GENERATED
CROSSING ANGLES
DIFFERENT DENSITIES
DIFFERENT SIZES
GRAPH DRAWING
MINIMIZING THE NUMBER OF
REAL-WORLD GRAPHS
TASK PERFORMANCE
DRAWING (GRAPHICS)
URI: http://elar.urfu.ru/handle/10995/90506
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 84915750123
WOS ID: 000354779600020
PURE ID: 434629
ISSN: 0302-9743
DOI: 10.1007/978-3-662-45803-7_20
metadata.dc.description.sponsorship: National Science Foundation, NSF: CCF-1115971
National Science Foundation, NSF: DEB-1053573
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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