Are we friends or enemies?: Let's ask thy neighbour!

Roshni Chakraborty, Nilotpal Chakraborty
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引用次数: 1

Abstract

With the richness of interactions among users emerging through different social media applications, drawing conclusive evidence about the sign of these relations (positive and negative) is receiving significant attention. In this paper, we propose an adaptive link prediction system which tactfully ensembles both local and nonlocal attributes of an edge to predict it's sign while considering the high variance of the network and handling the inherent sparsity of the graph. Experimental validation on signed networks, like Slash-dot and Epinions indicate the proposed approach can ensure high significant prediction accuracy when compared with the existing research works.
我们是朋友还是敌人?我们去问问你的邻居吧!
随着用户之间通过不同的社交媒体应用程序产生的丰富互动,得出关于这些关系(积极和消极)迹象的确凿证据受到了极大的关注。本文提出了一种自适应链路预测系统,该系统在考虑网络的高方差和图的固有稀疏性的同时,巧妙地综合了边缘的局部和非局部属性来预测其符号。在斜线点和Epinions等签名网络上进行的实验验证表明,与现有的研究成果相比,该方法可以保证较高的预测精度。
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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