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cs.LG2025
Topic Analysis with Side Information: A Neural-Augmented LDA Approach
Biyi Fang, Truong Vo, Kripa Rajshekhar +1
Traditional topic models such as Latent Dirichlet Allocation (LDA) have been widely used to uncover latent structures in text corpora, but they often struggle to integrate auxiliar…
cs.LG2022
Topic Analysis for Text with Side Data
Biyi Fang, Kripa Rajshekhar, Diego Klabjan
Although latent factor models (e.g., matrix factorization) obtain good performance in predictions, they suffer from several problems including cold-start, non-transparency, and sub…