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View all- Shen YJiang XLi ZWang YXu CShen HCheng X(2023)UniSKGRep: A unified representation learning framework of social network and knowledge graphNeural Networks10.1016/j.neunet.2022.11.010158(142-153)Online publication date: Jan-2023
Unsupervised network embedding using neural networks garnered considerable popularity in generating network features for solving various network-based problems such as link prediction, classification, clustering, etc. As majority of the ...
Given the heterogeneity of real-world networks and the low efficiency of directly mining networks, heterogeneous information network (HIN) representation learning, which learns low-dimensional embeddings of nodes to represent various structural ...
Heterogeneous network embedding aims to embed the networks into low dimensional spaces, in which each vertex is represented as a low-dimensional vector. Compared with homogeneous graphs, heterogeneous graphs increase the complexity of ...
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