Proximity-based Methods for Link Prediction in Graphs with R package 'linkprediction'

Ask Pub Date : 2020-01-01 DOI:10.18061/ASK.V29I1.0002
M. Bojanowski, Bartosz Chrol
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引用次数: 4

Abstract

Link prediction is a problem of predicting future edges of an undirected graph based on a single snapshot of data of that graph. Vertex proximity measures are indicies giving numerical scores for every pair of vertices in a graph that can be used for predicting future edges. This short note describes an R package ‘linkprediction’ implementing 20 different vertex similarity and proximity measures from the literature. The article provides the de fi nitions of implemented measures, describes the main user-facing functions, and illustrates the use of the methods with a problem of predicting future co-authorship relations between researchers of the University of Warsaw.
基于邻近度的图中链接预测方法
链接预测是基于无向图的单个数据快照来预测无向图的未来边缘的问题。顶点接近度量是为图中每对顶点给出数值分数的指标,可用于预测未来的边缘。这篇短文描述了一个R包“链接预测”,实现了20种不同的顶点相似度和接近度度量。本文提供了实施措施的定义,描述了主要的面向用户的功能,并举例说明了预测华沙大学研究人员之间未来合作关系的方法的使用问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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