DynACPD Embedding Algorithm for Prediction Tasks in Dynamic Networks
Chris Connell,
Yang Wang
Abstract:Classical network embeddings create a low dimensional representation of the learned relationships between features across nodes. Such embeddings are important for tasks such as link prediction and node classification. In the current paper, we consider low dimensional embeddings of dynamic networks, that is a family of time varying networks where there exist both temporal and spatial link relationships between nodes. We present novel embedding methods for a dynamic network based on higher order tensor decomposi… Show more
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