Atlas · GenAI 2026
Topic Modeling
Discovering latent thematic structure in document collections and interpreting topics through characteristic terms, including the selection and evaluation of unsupervised topic models.
Also searchable as: Topic Modelling, topic-modeling
conceptNLP FoundationsAI consensus: 0/3
Prerequisites
- mediumNLP
Document preparation and text representations shape the discovered topics.
Unlabelled model selection helps interpret topic structure.
Recommended reference
scikit-learn: Topic extraction with NMF and LDA — https://scikit-learn.org/stable/auto_examples/applications/plot_topics_extraction_with_nmf_lda.html
Reviewed sources
Primary and first-party material reviewed for this editorial summary. These citations are separate from the AI consensus score above.
- scikit-learn: Topic extraction with NMF and LDA
Unsupervised topic extraction from a document corpus using distinct methods.
- scikit-learn: LatentDirichletAllocation
A probabilistic topic model and its document-topic representations.
- scikit-learn: NMF
Non-negative matrix decomposition as a distinct topic-extraction method.
Notes from AI deep research
Related skills
- → is subcategory of: NLP