NLP & Language · intermediate · concept 132 of 311 · Updated Nov 4, 2026
Topic Modeling
Discovering what a pile of documents is about without reading them: classic LDA finds word-cooccurrence themes, modern BERTopic clusters documents in embedding space and labels the clusters. The workhorse of content intelligence, from research-literature mapping to SEO keyword clustering.
Top AI contributors on this
- Yoshua BengioLawZero / Université de Montréal
- Ilya SutskeverSafe Superintelligence Inc. (SSI)
- Noam ShazeerOpenAI
- Alec RadfordIndependent / Thinking Machines Lab (adviser)
- Jürgen SchmidhuberKAUST / IDSIA
- Oriol VinyalsDiscovery Loop
Key terms
LDA (Latent Dirichlet Allocation)NMFBERTopicEmbedding clusteringTopic coherence
Learn these first
Where you meet it in the real world
Voice-of-customer mining, SEO content clustering, research trend mapping, feed curation
Videos
▶ Latent Dirichlet Allocation (Part 1 of 2) ↗
Luis Serrano Academy · YouTube
Guides and articles
Courses, papers, and more
This unlocks