Hyperbolic graph topic modeling network with continuously updated topic tree

Connectivity across documents often exhibits a hierarchical network structure. Hyperbolic Graph Neural Networks (HGNNs) have shown promise in preserving network hierarchy. However, they do not model the notion of topics, thus document representations lack semantic interpretability. On the other hand...

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Bibliographic Details
Main Authors: ZHANG, Ce, YING, Rex, LAUW, Hady Wirawan
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2023
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Online Access:https://ink.library.smu.edu.sg/sis_research/8309
https://ink.library.smu.edu.sg/context/sis_research/article/9312/viewcontent/kdd23.pdf
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Institution: Singapore Management University
Language: English