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arXiv · 2210.08559

Coordinated Topic Modeling

Pritom Saha Akash·Jie Huang·Kevin Chen-Chuan Chang
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Abstract

We propose a new problem called coordinated topic modeling that imitates human behavior while describing a text corpus. It considers a set of well-defined topics like the axes of a semantic space with a reference representation. It then uses the axes to model a corpus for easily understandable representation. This new task helps represent a corpus more interpretably by reusing existing knowledge and benefits the corpora comparison task. We design ECTM, an embedding-based coordinated topic model that effectively uses the reference representation to capture the target corpus-specific aspects while maintaining each topic's global semantics. In ECTM, we introduce the topic- and document-level supervision with a self-training mechanism to solve the problem. Finally, extensive experiments on multiple domains show the superiority of our model over other baselines.

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Pritom Saha Akash, Jie Huang, Kevin Chen-Chuan Chang. 2022-10-22. Coordinated Topic Modeling. https://arxiv.org/abs/2210.08559

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