nlp:topic_modeling
Table of Contents
Topic Modeling
Topic modeling is used to analyze the distribution of words in documents. It assigns sets of words to “topics,” where each document contains one or more topics. Usually the topic assignments for words and documents is done using unsupervised methods, and doesn't correspond to a particular definition of topics. A popular method for topic modeling is Latent Dirichlet Allocation (LDA, Blei 2003).
Overviews
- Surveys
Papers
- Classic Papers
- Recent papers
- Applications
Software
People
Related Pages
nlp/topic_modeling.txt · Last modified: 2023/09/06 09:33 by jmflanig