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arXiv · 1811.10734

DynamicGEM: A Library for Dynamic Graph Embedding Methods

Palash Goyal·Sujit Rokka Chhetri·Ninareh Mehrabi·Emilio Ferrara·Arquimedes Canedo
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Abstract

DynamicGEM is an open-source Python library for learning node representations of dynamic graphs. It consists of state-of-the-art algorithms for defining embeddings of nodes whose connections evolve over time. The library also contains the evaluation framework for four downstream tasks on the network: graph reconstruction, static and temporal link prediction, node classification, and temporal visualization. We have implemented various metrics to evaluate the state-of-the-art methods, and examples of evolving networks from various domains. We have easy-to-use functions to call and evaluate the methods and have extensive usage documentation. Furthermore, DynamicGEM provides a template to add new algorithms with ease to facilitate further research on the topic.

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Palash Goyal, Sujit Rokka Chhetri, Ninareh Mehrabi, Emilio Ferrara, Arquimedes Canedo. 2018-11-26. DynamicGEM: A Library for Dynamic Graph Embedding Methods. https://arxiv.org/abs/1811.10734

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