In this paper, we propose HiWalk to learn distributed vector representations of the nodes in heterogeneous networks.

In this paper, we propose HiWalk to learn distributed vector representations of the nodes in heterogeneous networks. HiWalk is inspired by the state-of-the-art ...

In this paper, we propose HiWalk to learn distributed vector representations of the nodes in heterogeneous networks. HiWalk is inspired by the state-of-the-art ...

Results:In this study, we present a comprehensive benchmarking of supervised-learning for network-based gene classification, evaluating this approach and a ...

HiWalk: Learning node embeddings from heterogeneous networks. record by Linjing Li • HiWalk: Learning node embeddings from heterogeneous networks. Jie Bai ...

Sep 13, 2021 · Abstract—With different types of nodes and edges, heterogeneous networks have higher levels of structural diversity than homogeneous ...

Node representation learning is the task of extracting concise and informative feature embeddings of certain entities that are connected in a network. Many real ...

Sep 30, 2019 · Zeng, “Hiwalk: Learning node embeddings from heterogeneous networks,”. Information Systems, vol. 81, pp. 82–91, 2019. [45] T. Derr, Y. Ma ...

Missing: HiWalk: | Show results with:HiWalk:

Mar 15, 2022 · HiWalk: Learning node embeddings from heterogeneous networks ... A method of learning embeddings for given type of nodes in heterogeneous networks ...