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A New Link Prediction Algorithm Based on Local Links

机译:一种基于局部链接的链接预测新算法

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摘要

Link prediction refers to estimating the possibility of the existence of non-existent links between the nodes. The link prediction algorithms based on local information merely consider nodes' attributes or a small amount of topology information about common neighbors. In this paper, we proposed a new measure motivated by the cohesion between common neighbors and the predicted nodes-LNL (Local Neighbors Link). Experiments show that, compared with four classical algorithms on seven real networks, LNL has the higher accuracy and robustness. Furthermore, we apply the link prediction algorithms into large-scale networks. We implement the LNL method in both MapReduce and Spark, the experiments show that the implementation by Spark has higher efficiency than using MapReduce.
机译:链接预测是指估计节点之间不存在链接的可能性。基于局部信息的链路预测算法仅考虑节点的属性或有关公共邻居的少量拓扑信息。在本文中,我们提出了一种新措施,该措施受公共邻居与预测节点LNL(本地邻居链接)之间的凝聚力的影响。实验表明,与七个真实网络上的四个经典算法相比,LNL具有更高的准确性和鲁棒性。此外,我们将链接预测算法应用于大规模网络。我们在MapReduce和Spark中都实现了LNL方法,实验表明,与使用MapReduce相比,Spark的实现效率更高。

著录项

  • 来源
    《Web-age information management》|2015年|16-28|共13页
  • 会议地点 Qingdao(CN)
  • 作者单位

    Key Lab of Intelligent Telecommunication Software and Multimedia, Beijing University of Posts and Telecommunications, 100876 Beijing, China;

    Key Lab of Intelligent Telecommunication Software and Multimedia, Beijing University of Posts and Telecommunications, 100876 Beijing, China;

    Key Lab of Intelligent Telecommunication Software and Multimedia, Beijing University of Posts and Telecommunications, 100876 Beijing, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Link prediction; Complex network; Adjacent nodes; Parallel algorithm; Spark;

    机译:链接预测;复杂的网络;相邻节点;并行算法火花;

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