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Arxiv
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ffstruc2vec: Flat, Flexible and Scalable Learning of Node Representations from Structural Identities
- ffstruc2vec is a scalable deep-learning framework for learning node embedding vectors in a graph
- It aims to preserve various types of structural patterns suitable for different downstream application tasks
- ffstruc2vec outperforms existing approaches in both unsupervised and supervised tasks
- The framework provides interpretability by quantifying the influence of individual structural patterns on task outcomes
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