有限窗口大小下的双方图可视化

IF 0.4 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Alon Efrat, William Evans, Kassian Köck, Stephen Kobourov, Jacob Miller
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引用次数: 0

摘要

二部图通常用于可视化物体及其特征。一个对象可以具有多个特征,多个对象可以共享一个共同特征。二部图的标准可视化,对象和特征在整数坐标的两条平行线(比如水平)上,边缘绘制为线段,通常很难处理。在这种图形的可视化中,一个常见的任务是考虑一个对象及其所有特征。这自然定义了一个绘图窗口,定义为包含对象的x坐标及其所有特征的最小间隔。我们表明,如果对象和特征都可以重新排序,最小化平均窗口大小是np困难的。然而,如果特征是固定的,那么我们提供了一个有效的多项式时间算法来排列对象,从而最小化平均窗口大小。最后,我们介绍了一种不同的可视化二部图的方法,即将两部分的节点放置在两个同心圆上。对于这种设置,我们还展示了一般情况下的np -硬度,以及特征固定时的多项式时间算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visualization of bipartite graphs in limited window size

Bipartite graphs are commonly used to visualize objects and their features. An object may possess several features and several objects may share a common feature. The standard visualization of bipartite graphs, with objects and features on two (say horizontal) parallel lines at integer coordinates and edges drawn as line segments, can often be difficult to work with. A common task in visualization of such graphs is to consider one object and all its features. This naturally defines a drawing window, defined as the smallest interval that contains the x-coordinates of the object and all its features. We show that if both objects and features can be reordered, minimizing the average window size is NP-hard. However, if the features are fixed, then we provide an efficient polynomial-time algorithm for arranging the objects, so as to minimize the average window size. Finally, we introduce a different way of visualizing the bipartite graph, by placing the nodes of the two parts on two concentric circles. For this setting we also show NP-hardness for the general case and a polynomial-time algorithm when the features are fixed.

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来源期刊
Acta Informatica
Acta Informatica 工程技术-计算机:信息系统
CiteScore
2.40
自引率
16.70%
发文量
24
审稿时长
>12 weeks
期刊介绍: Acta Informatica provides international dissemination of articles on formal methods for the design and analysis of programs, computing systems and information structures, as well as related fields of Theoretical Computer Science such as Automata Theory, Logic in Computer Science, and Algorithmics. Topics of interest include: • semantics of programming languages • models and modeling languages for concurrent, distributed, reactive and mobile systems • models and modeling languages for timed, hybrid and probabilistic systems • specification, program analysis and verification • model checking and theorem proving • modal, temporal, first- and higher-order logics, and their variants • constraint logic, SAT/SMT-solving techniques • theoretical aspects of databases, semi-structured data and finite model theory • theoretical aspects of artificial intelligence, knowledge representation, description logic • automata theory, formal languages, term and graph rewriting • game-based models, synthesis • type theory, typed calculi • algebraic, coalgebraic and categorical methods • formal aspects of performance, dependability and reliability analysis • foundations of information and network security • parallel, distributed and randomized algorithms • design and analysis of algorithms • foundations of network and communication protocols.
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