ConceptUnsupervised Topic Modeling / 主题建模 / LDA
Unsupervised Topic Modeling
An NLP approach that automatically discovers latent thematic structures from large text corpora without requiring human-predefined categories. Representative algorithms include LDA (Latent Dirichlet Allocation) and BERTopic, which infer discussion topics by analyzing word co-occurrence patterns.
Timeline (last 90 days)
Sep 14
The study uses unsupervised topic modeling to automatically identify discussion topics from review text, then applies zero-shot classification to assign topics to the five food access dimensions.
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