深度潜在位置主题模型用于文本边网络的聚类和表示（英文版）

英文标题：The Deep Latent Position Topic Model for Clustering and Representation of Networks with Textual Edges中文摘要：本研究介绍了一种基于概率模型和可变图自动编码器方法的 Deep-LPTM 模型聚类策略，使节点和边在两个嵌入空间中构建联合表示，以解决社交网络中的节点聚类和数据可视化等问题，并在 Enron 公司的电子邮件数据上进行了验证。英文摘要：Numerical interactions leading to users sharing textual content published byothers are naturally represented by a network where the individuals areassociated with the nodes and the exchanged texts with the edges. To understandthose heterogeneous and complex data structur