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A Forwarding Prediction Model of Social Network based on Heterogeneous Network

机译:基于异构网络的社交网络转发预测模型

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Weibo and other online social networks have be-come the basic platform for information dissemination and diffusion. Prediction of information forwarding in social networks has attracted a lot of research work, especially how to effectively consider the characteristics of users and information, as well as the interaction between them. In this paper, we construct a weighted heterogeneous network based on users and information, and propose an improved heterogeneous network graph representation algorithm Mpath-wMetapath2vec to generate low dimensional representation for forwarding prediction. The experimental results on Weibo dataset show that our model outperforms the algorithms without considering node features and other graph vector representation algorithms.
机译:Weibo和其他在线社交网络已成为信息传播和扩散的基本平台。社交网络中信息转发的预测吸引了很多研究工作,特别是如何有效地考虑用户和信息的特征,以及它们之间的互动。在本文中,我们基于用户和信息构建加权异构网络,并提出改进的异构网络图形表示算法MPATH-WomeApath2VEC以产生用于转发预测的低维度表示。微博数据集的实验结果表明,我们的模型优于算法而不考虑节点特征和其他图形矢量表示算法。

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