Approximate personalized propagation for unsupervised embedding in heterogeneous graphs

Graphs are effective for representing various relationships in the real world and have been successfully applied in many areas, such as publication citations and movie networks. Compared to homogeneous graphs (i.e., nodes and edges of a single relation type), heterogeneous graphs have heterogeneity...

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Bibliographic Details
Main Authors: Chen, Yibi, Hu, Yikun, Li, Keqin, Yeo, Chai Kiat, Li, Kenli
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2022
Subjects:
Online Access:https://hdl.handle.net/10356/163878
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Institution: Nanyang Technological University
Language: English

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