Dynamic topic models for temporal document networks

Dynamic topic models explore the time evolution of topics in temporally accumulative corpora. While existing topic models focus on the dynamics of individual documents, we propose two neural topic models aimed at learning unified topic distributions that incorporate both document dynamics and networ...

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Main Authors: ZHANG, Ce, LAUW, Hady Wirawan
格式: text
語言:English
出版: Institutional Knowledge at Singapore Management University 2022
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在線閱讀:https://ink.library.smu.edu.sg/sis_research/7607
https://ink.library.smu.edu.sg/context/sis_research/article/8610/viewcontent/icml22.pdf
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