Temporal Network Representation Learning via Historical Neighborhoods Aggregation

30 Mar 2020Shixun HuangZhifeng BaoGuoliang LiYanghao ZhouJ. Shane Culpepper

Network embedding is an effective method to learn low-dimensional representations of nodes, which can be applied to various real-life applications such as visualization, node classification, and link prediction. Although significant progress has been made on this problem in recent years, several important challenges remain, such as how to properly capture temporal information in evolving networks... (read more)

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