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Sitting Closer to Friends Than Enemies, Revisited

机译:坐在靠近朋友而不是敌人,重新审视

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摘要

Signed graphs, i.e., undirected graphs with edges labelled with a plus or minus sign, are commonly used to model relationships in social networks. Recently, Kermarrec and Thraves [13] initiated the study of the problem of appropriately visualising the network: They asked whether any signed graph can be embedded into the metric space R~l in such a manner that every vertex is closer to all its friends (neigh-bours via positive edges) than to all its enemies (neighbours via negative edges). Interestingly, embeddability into R~1 can be expressed as a purely combinatorial problem. In this paper we pursue a deeper study of this case, answering several questions posed by Kermarrec and Thraves. First, we refine the approach of Kermarrec and Thraves for the case of complete signed graphs by showing that the problem is closely related to the recognition of proper interval graphs. Second, we prove that the general case, whose polynomial-time tractability remained open, is in fact NP-complete. Finally, we provide lower and upper bounds for the time complexity of the general case: we prove that the existence of a subexponential time (in the number of vertices and edges of the input signed graph) algorithm would violate the Exponential Time Hypothesis, whereas a simple dynamic programming approach gives a running time single-exponential in the number of vertices.
机译:符号图形,即用Plus或负符号标记的边缘的无向图形,通常用于在社交网络中建模关系。最近,Kermarrec和Thraves [13]开始研究适当可视化网络的问题:他们询问是否可以将任何签名的图形嵌入到公制空间R〜L中,使每个顶点更接近所有朋友(通过正边缘的邻居)比其所有敌人(邻居通过负面边缘)。有趣的是,将嵌入性进入R〜1可以表示为纯粹的组合问题。在本文中,我们追求了对这种情况的更深入研究,回答了Kermarrec和Thrives构成的几个问题。首先,我们通过表明问题与适当的间隔图的识别密切相关,优化Kermarrec的方法并为完整签名的图表的情况。其次,我们证明,常规案例,其多项式途径仍然是开放的,实际上是NP-Complete。最后,我们为一般情况的时间复杂度提供了下限和上限:我们证明了子统计时间的存在(在输入签名图的顶点和边缘的数量)算法将违反指数时间假设,而a简单的动态编程方法在顶点的数量中提供了一个运行的时间单指数。

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