GHTM: A graph-based hybrid topic modeling approach for Bengali language

arXiv:2508.00605 · cs.CL · Submitted 2025-08-01 · Read on arXiv

cs.CL

Submitted: 2025-08-01

Updated: 2026-10-12

Code: https://github.com/DULL-IIT/GHTM

Terminology

• Benchmark — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Generalization — 1× in this paper · explained in 13 episodes
• Graph Convolutional Networks — 1× in this paper
• Graph-based Hybrid Topic Model — 1× in this paper
• Non-negative Matrix Factorization — 1× in this paper

Sources

• Autoencoding Variational Inference For Topic Models
• Top2Vec: Distributed Representations of Topics
• BERTopic: Neural topic modeling with a class-based TF-IDF procedure
• Graph Contrastive Topic Model
• Potrika: Raw and Balanced Newspaper Datasets in the Bangla Language with Eight Topics and Five Attributes
• Mixing Dirichlet Topic Models and Word Embeddings to Make lda2vec
• Improving a tf-idf weighted document vector embedding

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